The most effective options. Analysis of the best and most efficient use of the subject of assessment. I came up with a model to advise a client

2. Real estate appraisal

2.7. Features of land valuation

2.7.3. Analysis of the best and most efficient land use

When evaluating land plot the option of its best and most effective use should be determined, which is determined by the interaction of a number of factors.

Analysis best use includes the study of alternative options for the use (development, development) of the land plot and the choice of the optimal one. This takes into account the prospects of the location, the state of market demand, the cost of development, the stability of the estimated income, etc.

When assessing the value of an object consisting of a land plot and buildings, great importance is attached to the analysis of the best use, firstly, of the alleged vacant land plot and, secondly, the land plot with existing improvements.

The analysis of the alleged vacant land plot is a necessary step in determining its value, and it is based on establishing the most profitable option for the use of land.

Analysis of a land plot with existing improvements involves making a decision on the demolition, modernization or preservation of the improvements available on the land plot in order to ensure maximum profitability of the object.

The probable and most profitable use of the site provides its highest value. Use cases must be legal, physically acceptable, and cost effective.

Let's name the main factors that determine the optimal use of land:

1) location - a factor that has a major impact on the value of a land plot (taking into account the prospects of the location, transport accessibility, the nature of the environment);

2) market demand - a factor reflecting the ratio of supply and demand in the market;

3) financial feasibility - the ability of the project to provide income from the use of the land plot, which would be sufficient to reimburse the costs of investors and ensure the receipt of the expected profit;

4) physical suitability of the site - the prospect of creating improvements - size, topography, soil quality, climate, geotechnical and hydrogeological characteristics of the site, existing zoning, environmental parameters, etc .;

5) technological feasibility and physical feasibility - analysis of the ratio of quality, costs and timing of the project, the likelihood of natural disasters, the availability of transport, the ability to connect to utilities, taking into account the size and shape of the site, for example, the size may be small for the construction of an industrial facility;

6) legislative (legal) admissibility - compliance of the option of using the land plot with the current legislation. It is revealed as a result of an analysis of building, environmental standards, restrictions on the number of storeys, the presence of temporary bans on construction in a given place, difficulties in the area of \u200b\u200bhistorical urban development, a possible change in regulations, compliance with zoning rules, negative moods of the local population;

Holders of the patent RU 2543315:

The invention relates to computer technology, can be implemented on modern high-speed computers and used, for example, in the selection of effective options in search, recommendation systems, decision support systems, Internet networks, systems for automatic classification of data packets, and in other related areas. Implementation of the claimed invention may include storing information on physical media, magnetic disks, network storages of information, processing it on a computer and providing the resulting set of effective options to the end user in any form available to him.

Before presenting the invention, for convenience and unambiguous understanding, it is advisable to give the decoding and definitions of the designations and / or terms used below.

A search engine is a computer program designed to search for information on the Internet. The search is performed on the basis of an arbitrary text query generated by the user. Search results are presented to the user sorted in accordance with a certain characteristic of relevance to the query. Examples of search engines are Bing, Google, Yahoo, Yandex.

A recommendation system is a computer program that selects from the entire set of presented alternatives (options) those that may be most interesting to a specific user, based on a number of characteristics, for example, a query entered by the user in a search engine. It should be noted that in most cases, recommender systems present the result either as a set of recommended options, or as a ranking of all or part of the presented options. Thus, the methods of processing and transforming information within the framework of recommender systems work in related areas, such as, for example, the problem of assessing the efficiency of enterprises, etc.

The principle of superposition (in this context, in contrast to the well-known principle of superposition in physics) consists in the sequential exclusion of variants from the original set using procedures that may be different at each stage of exclusion. An example of procedures is given in Appendix 1. At the first stage, the elimination is made from the entire initial set of options, at the second stage, the input set is the effective options identified at the first stage, and so on.

Effective ("good") elements (options) are those elements that are the best, most preferable, most useful according to the given parameters for solving specific problems in which it is necessary to rank options, and to meet the information needs of users (people, specialists, agents ).

Ineffective ("bad") elements (options) are those elements that certainly never (under any circumstances) can not be used to solve specific problems, since there are more preferable options for their solution.

The value of efficiency, with the help of which the rules for selection and ranking of options are constructed, is set by an expert.

Most search engines have data storage and processing facilities that contain such performance (relevance) estimates for large representative sets of queries and search results for these queries. In such tools, a query and search results for it (variants) are represented by their sets of criteria and an assessment of the relevance of search results, set by experts.

There are various formal criteria for assessing the relevance of a search element to a search query, given constructively (such as the frequency of the use of a word in the text or the TF-IDF criterion, which is the frequency of the use of query words in the text, taking into account the degree of importance of each word). Note that such formal criteria are more likely algorithms by which existing search engines actually perform a search than independent criteria evaluating the results of this search. The scores calculated by such formal criteria may still be very different from the relevance scores given by experts.

At the moment, there are three main methods by which the selection and ranking of options occurs.

There is a known method for selecting and ranking options, which consists in the fact that each option is assigned an absolute assessment of the degree of "importance" using values \u200b\u200bfor several criteria. The most common way is to build a regression.

In addition, the McRank classification method can be used to rank options, the essence of which is to calculate the so-called "expected relevance" for each request-document pair as a function of the probability of belonging to the relevance classes obtained as a result of the classification. As a result of calculating the "expected relevance", the ranking of the "request-document" pair within each query occurs in descending order of the "expected relevance" (L. Ping, C.J.S. Burgess, K. By - McRank: Learning ranking using multivariate analysis and gradient acceleration enumeration. NIPS. Curran Associates. 2007-).

There is a known method of choosing alternatives, which consists in pairwise comparison of two options in order to identify the best of them. Based on the formation of such relations, an order is built with the help of which the options are selected.

An example of a known method is the support vector machine, which consists in translating the original vectors into a space of a higher dimension and finding separating hyperplanes with a maximum gap in this space (K. Cortes, Vapnik V.N., Support vector machine, "Machine Learning" magazine, 20, 1995 - [C. Cortes, Vapnik VN; "Support-Vector Networks", Machine Learning, 20, 1995]), as well as other methods such as:

RankNet (Microsoft Bing search engine, C.J.S. Burgess, T. Shakde et al. "Teaching Ranking Using Gradient Descent", ISML, 2005: 89-96 -), the essence of which is to use a "neural network" and a probabilistic cost function for ranking search results,

RankBoost (J. Freund, R. Jere, R. E. Chapae and J. Singer. An efficient search acceleration algorithm for combined preferences, Journal of Machine Learning Research, 4: 933-969, 2003 -), which is based on the procedure sequential construction of a composition of machine learning algorithms for classifying pairs of documents.

FRank (M. Tsai, T.-Y. Liu, et al. FRank: A Ranking Method with Fidelity, SIGIR 2007 - [M. Tsai, T.-Y. Liu, et al. FRank: A Ranking Method with Fidelity Loss, SIGIR 2007]), which is a modification of the RankNet method, however, instead of entropy values, the distribution accuracy function is used as a cost function, and others.

There is a known method for choosing alternatives, which consists in a list comparison of options. In this case, the filtering of the entire set of alternatives is performed according to the specified rules.

Examples of this method include:

1. A tree construction method, minimization of the penalty function ListNet, in which a probability space is introduced on a set of permutations. The entropy function on the entered space is used as a loss function. (Zhe Cao, Tao Kin, Tai-Yan Liu, Ming-Feng Tsai and Hang Li. Teaching Ranking: From Pairwise to List Approach, 2007-),

2. The method of list comparison of RankCosine variants, which uses a loss function based on the similarity of the cosine of the angle between the ranked list and the original list of the training sample, to rank the search results (T.Kin, H.-D. Zhang, M.-F. Tsai, D.-S. Wang, T.-Ya. Leeu, H. Lee: Request-Dependent Loss Functions for Information Retrieval. Inf. Process. Manage. 44 (2): 838-855, 2008 - [T. Qin, X.-D. Zhang, M.-F. Tsai, D.-S. Wang, T.-Y. Liu, H. Li: Query-level loss functions for information retrieval. Inf. Process. Manage. 44 (2): 838-855, 2008)],

3. The AdaRank ranking method, in which the AdaBoost machine learning algorithm is used to construct the ranking function, which constructs a linear combination of classifiers to improve the ranking model. (Yu Hu, X. Lee. AdaRank: a brute force algorithm for information retrieval. SIGIR 2007 -),

4. The SoftRank ranking method, the essence of which is direct optimization of nonsmooth ranking metrics, (Mike Taylor, John Guyver, Steven Robertson, Tom Minka. SoftRank: Optimization of nonsmooth metrics, 2008-) and others.

All of these methods show fairly high accuracy in their highly specialized fields.

The disadvantages of the known methods of selecting variants are:

The use of complex selection procedures when working with large amounts of data, which leads to a significant increase in computational complexity;

Low accuracy in the selection and ranking of options using a large number of criteria and / and with a large number of options.

Typically, with large amounts of data, the decision tree search method is used. It consists in constructing a sequence of threshold procedures with the help of which options are selected.

The disadvantage of the decision tree search method is the low reliability of the results, since the choice of threshold procedures as a method for selecting and ranking options is not always justified (effective). In addition, not one criterion, but a whole group (their combination) can be used simultaneously to select or rank options, which is not taken into account in the decision tree search method. Often, it is impossible to select or rank the entire list of options according to any one criterion (several criteria). In this regard, in order to rank variants with high accuracy, it is necessary to construct a large number of such trees, and the results of their work must be aggregated.

Known methods according to the patent of the Russian Federation No. 2435212 "Collecting data on user behavior in web search to increase the relevance of the search", the patent of the Russian Federation No. 2443015 "Ranking functions using a modified Bayesian classifier of queries with incremental updates", according to the RF patent No. methods of ranking documents based on structurally interrelated information ", which consist in collecting additional information, namely in using a Bayesian classifier, collecting information about user behavior, information about the structural relationships of documents, with the help of which the selection and ranking of options is carried out. The disadvantage of the known methods is the complication of existing methods of selection and ranking of options by adding new criteria.

The closest in technical essence and the achieved result is a method for calculating a temporary weight for a search result, which consists in identifying a user event corresponding to a search result, and the user event has an event start time, an event end time and an event duration; determining the current time; and determining the time weight for this search result based on the temporal proximity of the current time to the user event. The method assumes that the time weight changes over time, increases exponentially as the current time approaches the start time of the event, is constant over the duration of the event, peaks at a point in time during the duration of the event, and decreases exponentially when the current time is removed. from the end time of the event. The method is designed to search for information on the Internet using a temporary weight to rank search results. (RF patent No. 2435213, IPC G06F 17/30, publ. 27.11.2011).

The disadvantage of the known method, as well as similar existing technologies for searching on demand on the Internet, is that they, as a rule, use "rough" algorithms for selection and ranking, i.e. algorithms with linear computational complexity O (n), where n is the number of options. As a rule, this complexity is achieved by the fact that the developed selection and ranking rules are simplified (more precisely, they are roughened) in order to provide an acceptable level of complexity. In this case, the result achieved with such methods is of lower quality.

The technical problem to be solved by the claimed invention consists in creating a new method for better selection and ranking of effective options, providing a high selection rate and high accuracy of results.

The technical problem posed is solved by the fact that according to the proposed invention, the method for selecting and ranking effective options according to the first embodiment consists in the fact that the criteria for assessing the relevance of a variant to a search query are preliminarily formed and a finite number of options or a set of procedures for selecting and ranking options and the sequence of their execution for selecting the options evaluated as the most effective, evaluating each of the options according to their relevance to the search query criteria, on the basis of which the options are ranked by assigning a rank to each of them from the condition of meeting the greatest number of criteria in descending order; the selection and ranking of options are sequentially carried out by the superposition method in at least two stages, if the number of options in the remaining group of options corresponds to a predetermined finite number of options for selection or all specified selection procedures are used, the selection of options and their ranking is stopped and options from the selected group are evaluated as the most effective, if the number of options in the remaining group of options does not correspond to the predetermined finite number of options for selection, the selection of options and their ranking continues, while the selection of options, their ranking and exclusion are carried out until the specified number of options is reached or until all specified selection procedures will not be used and the selected group of options is assessed as the most effective.

The claimed method according to the first embodiment is characterized by the following additional essential features:

At the second and subsequent stages, criteria for evaluating the search query are formed, on the basis of which the options are ranked and the options are selected from the remaining array processed at the previous stage by the superposition method using methods whose computational complexity is not less than quadratic O (n 2) and exclude the following group of options with a lower rank.

The technical problem posed is solved by the fact that according to the proposed invention, the method for selecting and ranking effective options according to the second embodiment consists in the fact that the criteria for assessing the relevance of the option to the search query are preliminarily formed and a finite number of options for selection are set, evaluated as the most effective, each of variants by relevance to the search query criteria, on the basis of which the variants are ranked by assigning a rank to each of them from the condition of meeting the greatest number of criteria in descending order; the selection and ranking of options are sequentially carried out by the superposition method in at least two stages, if the number of options in the remaining group of options corresponds to a predetermined finite number of options for selection, the selection of options and their ranking is stopped and options from the selected group are estimated as the most effective if the number options in the remaining group of options does not correspond to the predetermined finite number of options for selection, the selection of options and their ranking continues, while the selection of options, their ranking and exclusion are carried out until the specified number of options is reached, the selected group of options is assessed as the most effective ...

The claimed method according to the second embodiment is characterized by the following additional essential features:

At the first stage, the selection of options is carried out in the presence of a large number of them by the superposition method using the selection and ranking methods characterized by linear computational complexity O (n), and the group of options that have the lowest rank are excluded;

At the second and subsequent stages, criteria for evaluating the search query are formed, on the basis of which the options are ranked and the options are selected from the remaining array processed at the previous stage by the superposition method using methods whose computational complexity is not less than quadratic O (n 2) and exclude the following group of options with a lower rank;

the method additionally defines a set of procedures for selecting and ranking options and the sequence of their implementation.

The technical problem posed is solved by the fact that according to the proposed invention, the method for selecting and ranking effective options according to the third embodiment consists in the fact that the criteria for assessing the relevance of an option to a search query are preliminarily formed and a set of procedures for selecting and ranking options and the sequence of their execution for selecting options evaluated as the most effective, evaluate each of the options according to their relevance to the search query criteria, on the basis of which the options are ranked by assigning a rank to each of them from the condition of meeting the greatest number of criteria in descending order; the selection and ranking of variants are sequentially carried out by the superposition method, at least in two stages; the selection of variants, their ranking and elimination are carried out until all the given selection procedures are used and the selected group of variants is evaluated as the most effective.

The claimed method but the third embodiment is characterized by the following additional essential features:

At the first stage, options are selected if there are a large number of them by the superposition method using selection and ranking methods characterized by linear computational complexity O (n), and the group of options that have the lowest rank is excluded

At the second and subsequent stages, criteria for evaluating the search query are formed, on the basis of which the options are ranked and the options are selected from the remaining array processed at the previous stage by the superposition method using methods whose computational complexity is not less than the quadratic 0 (n2) and exclude the next group of options with lower rank.

Additionally, a finite number of selection options are specified, which are evaluated as the most effective;

To select the most effective group of options, additional selection and ranking methods and the sequence of their execution are set, and the selection and ranking are repeated.

The technical result, the achievement of which is ensured by the implementation of the entire claimed set of essential features of the method, consists in increasing the speed and accuracy (reliability) of the selection of effective options in search, recommendation systems due to the possibility, using the principle of superposition, to regulate the complexity of procedures for identifying effective options.

The essence of the invention is illustrated by Fig. 1, which shows a flow diagram for the implementation of the proposed method, where:

1 - initial set of options (many different options);

2 - the procedure for eliminating ineffective objects at the first stage using approximate methods;

3 - a set of options left after the first stage of selection;

4 - exclusion of ineffective options using exclusion procedures;

5 - consistent application of procedures for eliminating ineffective objects using approximate methods;

6 - a subset of options that does not contain ineffective options;

7 - the operation of ranking the group of options obtained at step 6 using both approximate and exact methods;

8 - the operation of assigning the lowest rank to all ineffective options and adding these options to the final list after the ranked options;

9 - providing the final ordered group of options to the end consumer;

10 shows a group of ineffective options, truncated using sequential superposition of elimination procedures.

The proposed method is based on the superposition method, which consists in the sequential elimination of previous options using some procedures, which may be different at each stage of elimination.

The inventive method is carried out as follows (figure 1).

A large set of options 1 exists or is being formed, which may include ineffective options.

The term "large set of options (search elements)" is considered within the framework of the concept of "Big Data", which appeared in connection with the development of information technologies and includes approaches to processing huge volumes of heterogeneous information.

A large set of options (search elements) within the framework of this concept means a structured or unstructured dataset of a huge volume and significant diversity.

In order to exclude ineffective options and select the most effective options, the criteria for assessing the relevance of a variant (search element) to a search query are preliminarily formed and, if necessary, a finite number of options (search elements) are set for selection, assessed as the most effective (as the most appropriate to the criteria for assessing relevance search query). Next, each of the options (search elements) is assessed according to their relevance to the search query criteria, on the basis of which the options (search elements) are ranked by assigning a rank to each of them from the condition of meeting the largest number of criteria in descending order. The selection and ranking of variants (search elements) is carried out sequentially according to the superposition method in at least two stages.

The method can be defined differently - a set of used selection and ranking methods and the sequence of their application can be specified.

At the first stage, options are selected from a large number (item 2 of Fig. 1) by the superposition method using selection and ranking methods, characterized by linear computational complexity O (n).

For this operation, well-known methods with linear computational complexity O (n) can be used, such as, for example, the relative majority rule, Borda's rule, the rule of overthreshold choice, and others. The most complete list of selection rules is given in Appendix 1.

As a result, two groups of variants are formed: a group of variants 10 having the lowest rank, and a group of variants 3 to be further analyzed.

The group of variants 10, which have the lowest rank, are excluded (item 4 of Fig. 1).

At the next stage, the criteria for evaluating the search query are formed, on the basis of which the options are ranked. The selection of options from the remaining processed array is carried out according to the superposition method (item 5 of Fig. 1) using methods whose computational complexity is not less than quadratic O (n 2).

For this operation, well-known methods can be used, the computational complexity of which is at least quadratic O (n 2), such as, for example, the minimal nondominated set, Richelson's rule, or rules based on the construction of a majority or tournament matrix (see Appendix 1).

The selection of options and their ranking is stopped and the options (search elements) from the selected group are evaluated as the most effective or promising when all the used (specified) methods of selection and ranking are fulfilled, or if the number of options in the remaining group of options corresponds to a predetermined finite number of options (search elements) for selection. The selection of options and their ranking can be carried out repeatedly by specifying additional methods of selection and ranking, as well as the sequence of their execution.

Otherwise, the selection and ranking continue to be carried out as described above (items 7 and 8 of Fig. 1). That is, the group of options 6 is ranked using the ranking operations 7, if necessary, you can add (item 8 of Fig. 1) options to it from the group of ineffective options 10. The selection of options (search elements), their ranking and elimination are carried out (item 9 of FIG. 1. Thus, there is a selection and ranking of effective options, their ranking and provision of these options to the final consumer.

The superposition approach is used when it is impossible to unambiguously determine by one criterion which options are effective and which are not. A distinctive feature of the method is the ability to identify, in the presence of a large number of criteria from a large number of options, those options that are effective, and also the ability to adjust the computational complexity of the proposed method. The inventive method allows you to go from complex mechanisms for identifying effective options to composite ones, which are a combination or superposition of simpler procedures. The results of the previous stages of selection and ranking are processed in the following stages of the method.

In addition, in the claimed method for ranking options, not one criterion can be simultaneously used, but a whole group of criteria (their combination), which is not taken into account, for example, in the well-known decision tree search method, which uses the simplest threshold procedures, the choice of which is not always justified.

In contrast to the known methods, the superposition method is quite flexible and allows you to vary the number of stages in the selection method.

The superposition approach excludes the possibility of losing effective options in the case of using approximate methods. After the successive composition of the exclusion stages, the remaining options are selected and ranked. All ineffective options that were excluded before the ranking procedure will have the lowest (worst) rank and will be selected (offered) for solving problems in the last place.

By approximate methods, which are used to reduce the number of options at high speed, we mean selection and ranking rules with linear computational complexity O (n). Such rules (methods) should use (read) the values \u200b\u200bof the parameters of each option (alternative) only such a number of times k that does not depend on the number of options (alternatives) n, and is significantly less than n. In the fastest (ideal) case for the rule with complexity O (n), each option is used only once. The rule has the ability to determine whether a variant is effective or not, based only on the data of this one variant, without comparing it with each of the other variants. For example, for the rule of discarding ineffective options, with values \u200b\u200b"below average" for some parameter (for which the values \u200b\u200bare, the higher the better), it is required to count the value of each option only 2 times: the first time to calculate the average, and the second time to determine if this option is higher or lower than the average. This rule applies to rules with linear computational complexity O (n).

Thus, the use of selection and ranking methods characterized by linear computational complexity O (n) provides a significant increase in the speed of selection of effective options in search and recommendation systems.

However, initially, it is rather difficult to use subtle (exact) methods for the entire range of options due to the large number of options. When using approximate procedures for cutting off ineffective options, the number of different options decreases, which ultimately leads to the possibility of using more subtle methods for selecting and ranking the remaining options.

Fine (precise) methods that are used when there are a small number of options are selection and ranking rules, the computational complexity of which depends solely on the number of times each option is used. There are rules that use pairwise "distances" between options (alternatives), in special scales. Such rules must enumerate all other options for each option, i.e. perform (n times n) actions, the computational complexity is quadratic. There are also rules that compare each option with all sorts of other options in order to more accurately determine the position of this option in relation to the rest. The computational complexity of such rules is even higher. We can say that rules with complexity, starting with a quadratic O (n 2), cannot be applied on the full set of options (in the millions) when solving the problem of search and ranking on the Internet, and in similar problems in other areas of activity, since computing the complexity of these rules strongly depends on the number of options available in the set.

Thus, the use of methods whose computational complexity is not lower than the quadratic O (n 2) provides a significant increase in the accuracy (reliability) of the selection of effective options in search and recommendation systems.

The advantage of the method is that it becomes possible to regulate the computational complexity of the procedure for identifying effective options. This means that if the application of some procedures required huge computational resources on a large amount of data, then after successive elimination of variants, the same procedures on the remaining subset can work rather quickly. In other words, by setting a certain limit on the amount of computational resources used to execute the method, it is possible to establish the number of stages that can be used to cut off obviously ineffective options using fast approximate methods, after which one can use rather laborious procedures that reveal effective options with sufficiently high precision. This is the control of the computational complexity of the method.

The inventive method can also be applied in the task of teaching ranking, that is, the task of choosing options with previously known estimates of their usefulness by criteria. The method allows to form, according to a previously known degree of utility (efficiency) of some options, rules for their selection and ranking (a set of used selection and ranking methods, as well as the sequence of their application), in accordance with which the selection and ranking of other options can be made, about the degree of utility ( efficiency) of which nothing is known.

The inventive method can be carried out using known hardware and software. The implementation of the proposed method includes:

1. Collection and storage of data /

2. Data processing, selection and ranking of options.

3. Providing results to the user.

Collection and storage of data. At this stage, the collection and storage of the necessary information about the existing options takes place. Option information can be collected from existing data sources, such as various existing information systems, websites, web services, other data servers, computer files, i.e. from all sources that store information about variants in a format suitable for further processing. Data collection can be performed using existing software that extracts data from external sources (for example, ETL systems or tools for collecting the content of web pages on the Internet), or implemented on a computer using any programming language, in particular, a programming language C, C ++, C #, Java, Python, PHP and many more. Information storage can be carried out both on a server or a group of servers using existing platforms that store data, and on any storage medium from which it is possible to further read the available information. Also, information storage can be carried out directly in the computer's RAM in the case when there is no need to permanently store information.

Data processing, including, according to the claimed method, the selection and ranking of options using approximate and accurate methods, is implemented using a computer, which makes ranking options and identifying the most effective of them. The stage of data processing can be performed both on the server and on the user's computer itself.

After completing the stage of data processing, the obtained results are provided to the end user in any format suitable for him. The results of the execution can be stored on the server, other media from which it is possible to read it further, or can be presented to the user's computer screen directly using a web browser or any other software tool with which information is viewed.

Examples of implementation of the method.

The problem of finding relevant pages on the Internet with selection and ranking based on the principle of superposition

The task of finding relevant pages on the Internet, ranking based on the idea of \u200b\u200bsuperposition can be implemented as follows. First, by quick (approximate) methods, obviously irrelevant pages are excluded. These irrelevant pages can be, for example, those pages that do not belong to the given topic, contain spam, viruses, advertisements, undesirable content for the user, phishing (Internet fraud) and others. Then, on the remaining significantly smaller set of pages, finer (accurate) ranking methods are applied, which, however, require more computational resources (slow). The irrelevant pages mentioned above can never be relevant to the user's request, which means that their use in more time-consuming methods is redundant and simply unnecessary. In this example, superposition of some set of fast, but approximate methods (used to cut off only the most irrelevant pages) and some set of exact methods (used for final ranking of a small number of alternatives) gives a gain in speed and accuracy (relevance) of the final ranking. In particular, there is no need for detailed ranking for irrelevant pages, it is enough to assign them all the same rank (the last place in the ranking).

Table 1 shows the simplest example of using two methods for choosing options - the Pareto rule and a four-step selection method based on the idea of \u200b\u200bsuperposition. In the task, it is necessary to determine which of the options are most relevant (suitable) to the entered user request. Each variant is evaluated according to three criteria: the number of words from the request in the head of the document, the number of words from the request in the entire document, the Boolean model (the presence of all the words of the request in the document). In the example, the selection is made from 29 options.

If the usual Pareto rule is used, then the relevant documents will be documents No. 2, 5, 6. When using the Pareto rule, each option must be compared with all other options, ie. each of the 29 options must be matched against each other. This means that the more options are in the sample, the greater the computational complexity of this rule, which leads to the need to use simpler (approximate) selection rules.

However, the Pareto rule can be applied if we use a method for selecting and ranking effective options based on the idea of \u200b\u200bsuperposition. Table 1 shows a four-step selection method, which consists of successively applying three suprathreshold rules, after which the Pareto rule is applied.

At the first stage, all variants (documents) are excluded, the title of which does not contain a single word from the request. Thus, the number of options is reduced from 29 to 8.

At the second stage, there is an exclusion of those variants for which not a single word from the query was found in the main part of the document. Then the number of options is reduced from 8 to 6. After that, only those documents are selected that contain all the words from the query. As a result, the number of options is reduced to 4. After that, the Pareto rule is applied for the remaining options, and the final choice includes only 3 options (documents) - No. 2, 5, 6.

In this example, the results of both methods are the same. However, the computational complexity of the Pareto rule is much higher. Therefore, if the number of options is small, the choice of the selection and ranking method is not fundamental (does not matter). However, in conditions when the number of variants reaches several million, it is necessary to use the second method based on the idea of \u200b\u200bsuperposition, since it allows you to combine simple and complex selection rules, which reduces the computational complexity of the method.

In a number of models, in order to present the most interesting and demanded proposal, participants in social networks need to segment user groups according to their common interests or the intensity of information exchange between them. In this case, for example, the cutoff according to the rule "no more than one contact in the last year" (for a certain set of goods and services) allows you to immediately narrow the number of options within the group to a level acceptable for more complex algorithms. Of course, having more than one contact per year does not imply common interests of users, i.e. obviously ineffective variants of grouping (segmentation) of social network participants according to their interests are cut off, with a simultaneous and sharp decrease in the group size.

Thus, the presented method allows selection and ranking of options with high accuracy, especially in the presence of a large number of options characterized by a large set of indicators, since it allows a combination of approximate and accurate procedures.

The claimed method can be used in the selection of effective options in search, recommendation systems, decision support systems, Internet networks, systems for automatic classification of data packets and in other related areas.

In addition, the invention can be used to solve the problem of teaching ranking, that is, the problem of choosing options with previously known estimates of their usefulness by criteria, for example, when assessing the efficiency of enterprises, retail outlets and other objects in related areas.

Appendix 1. List of selection rules given in the work of FT Aleskerov, E. Kurbanov "On the degree of manipulability of collective selection rules", Automation and Remote Control, 1998, No. 10, 134-146.

1. Plurality rule

The choice includes alternatives that are best for the largest number of criteria, i.e.

those. means the number of criteria for which the alternative a is at least the qth place in their ordering. Thus, if q \u003d 1, then a is the best alternative for criterion i; if q \u003d 2, then a - either the first or the second best alternative, etc. The number q will be called the level of the procedure.

those. alternatives are selected that are among the q best for the maximum number of criteria.

This selection rule has linear computational complexity; for ranking, the computational complexity of the rule depends on the value of q. For q<

3. Threshold rule

Let ν 1 (x) be the number of criteria for which the alternative x is the worst in their ordering, ν 2 (x) is the number of criteria for which the alternative x is the second worst, and so on, ν m (x) is the number of criteria, for which alternative x is best. The alternatives are then ordered lexicographically. They say that alternative x V - dominates alternative y if ν 1 (x)< ν 1 (y) или, если существует k≤m такое, что ν i (x)= ν i (y), i=1, …, k-1, и ν k (x)< k (y). Другими словами, в первую очередь сравниваются количества последних мест в упорядочениях для каждой альтернативы, в случае, когда они равны, идет сравнение количества предпоследних мест, и так далее. Выбором являются альтернативы, недоминируемые по V.

This selection and ranking rule has linear computational complexity.

4. Borda rule

Each alternative x∈A is associated with a number r i (x, P →) equal to the cardinality of the set of alternatives worse than x in the criterion P i ∈ P →, that is, r i (x, P →) \u003d | L i (x) | \u003d | (b ∈ A: x P i b) | ... The sum of these values \u200b\u200bfor i∈N is called the Borda rank for the alternative x,

Choice includes alternatives with maximum rank

5. Black's procedure

If there is a Condorcet winner, it is declared a collective choice, otherwise the Borda rule is used.

6. Coombs' procedure.

The option that is considered the worst by the maximum number of voters is excluded. Then the profile is narrowed down to a new set X and the procedure continues until there are only non-excludable variants. Note here the difference between Coombs' Rule and the Voice Transmission System. The Coombs Rule strikes out the worst options, while the transmission system strikes out the best options for the minimum number of voters.

This selection and ranking rule has linear computational complexity.

7. Hara procedure

For each alternative, the number of first places in the orderings by criteria is counted. Then the alternatives with the smallest number of first places drop out of the voting. The procedure is repeated until the choice remains non-empty.

This selection and ranking rule has linear computational complexity.

8. Reverse majority rule

The selection includes alternatives that are worst for the smallest number of criteria.

This selection and ranking rule has linear computational complexity.

9. Copland's first rule

For each alternative, two indicators are calculated: the sum of the number of alternatives that are worse than the specified for each criterion, and the sum of the numbers of alternatives that are better than the specified for each criterion. The collective choice includes alternatives with the greatest difference between these two indicators.

This selection rule has a linear computational complexity; for ranking, the computational complexity of the rule strongly depends on the input data and is quadratic in the worst case.

10. Reverse Borda procedure (with the transfer of votes)

For each alternative, the Borda rank is calculated. Then the alternative with the lowest rank is eliminated. Borda ranks are recalculated for a set of alternatives without a dropped alternative. The procedure is repeated until the selection is not empty.

For the choice, the computational complexity of the rule is quadratic at worst. For ranking, the computational complexity of the rule is not less than quadratic.

11. Nanson's rule

The rank of the Borda is calculated for all options. Then the average Borda score is calculated and only those x variants for which the Borda score is below average are excluded. Then the set X \u003d A \\ (x) is constructed, and the procedure is applied to the narrowed profile / X. The procedure continues until there are only non-excludable options. For the choice, the computational complexity of the rule is quadratic at worst. For ranking, the computational complexity of the rule is not less than quadratic.

12. Minimum dominant set

The set of alternatives Q is dominant if and only if any alternative from Q dominates any alternative outside Q by the majority relation.

A dominant set is minimal if none of its own subsets is dominant. The collective choice is the minimum dominant set, if there is one, or their union, if there are several. This rule for selection and ranking has a computational complexity of at least quadratic.

13. Minimum non-dominated set

The set of alternatives Q is undominated if and only if there is no alternative outside Q that dominates any alternative from the set Q.

An undominated set is minimal if none of its proper subsets is undominated. The collective choice is the minimum non-dominated set, if there is one, or their union, if there are several. This rule for selection and ranking has a computational complexity of at least quadratic.

14. Minimum weakly stable set

The set of alternatives Q is weakly stable if and only if the existence of an alternative y outside Q dominating an alternative x from Q implies the existence of an alternative z from Q such that z dominates Y-

A weakly stable set is minimal if none of its proper subsets is weakly stable. The collective choice is the minimum weakly stable set, if there is one, or their union, if there are several.

This rule for selection and ranking has a computational complexity of at least quadratic.

75. Fishburne Rule

Let us construct a new binary relation y, in which x dominates y if and only if the upper contour of the alternative x is a proper subset of the upper contour of the alternative y.

The collective choice will be a set of alternatives that are not dominated by y.

This rule for selection and ranking has a computational complexity of at least quadratic.

16. Uncovered set I.

Let us construct a new binary relation 5 in which x dominates y if and only if the lower contour of the alternative y is a proper subset of the lower contour of the alternative x.

The collective choice will be a set of alternatives not dominated by the relation 8.

This rule for selection and ranking has a computational complexity of at least quadratic.

17. Uncovered set II

Alternative x B - alternative y dominates if x is dominated by y by majority ratio and the upper contour of alternative x is a subset of the upper contour of alternative y. The collective choice includes alternatives that are not dominated by relation B. This selection and ranking rule has a computational complexity of at least quadratic.

18. Richelson's rule

A new binary relation σ is constructed in which x dominates y if and only if

The bottom contour y is a subset of the bottom contour x

Top path x is a subset of top path y

In one of the two above cases, the entry occurs as a "proper subset"

The collective choice includes non-dominated software alternatives.

This rule for selection and ranking has a computational complexity of at least quadratic.

19. Copland's first rule

The collective selection includes alternatives with the maximum power difference between the lower circuit and the upper circuit.

This rule for selection and ranking has a computational complexity of at least quadratic.

20. Copland's second rule

The collective choice includes alternatives with the maximum power of the lower circuit.

This rule for selection and ranking has a computational complexity of at least quadratic.

21. Copland's third rule

The collective choice includes alternatives with a minimum upper circuit power.

This rule for selection and ranking has a computational complexity of at least quadratic.

22. Two-step plurality rule

First, the simple majority rule is used (i.e., the option that receives more than 50% of the votes - the first places - in the ordering of voters is chosen). If such an option is found, then the procedure stops. If there is no such option, then two options are selected that have received more votes than other options (if there are more than two, then the two with the lowest numbers are taken). Then, assuming that the opinions of voters regarding these options (if the others are deleted) do not change, we again apply the rule of simple majority / votes - already on a two-element set.

Since individual opinions are presented in the form of linear orders, there is always (with an odd number of voters) a single winning option.

This selection and ranking rule has linear computational complexity.

First, the simple majority rule is used (i.e. the option that receives more than 50% of the votes is chosen). If such an option is found, then the procedure stops. If there is no such option, then option x with the minimum number of votes is deleted from the list.

Then the procedure is again applied to the set X \u003d A \\ (x and the profile / X This rule for selection and ranking has linear computational complexity.

24. Young's procedure

If there is a Condorcet winner for the profile, it is selected and the procedure stops there. If there is no such option, then all possible coalitions are considered, in which there are partial Condorcet winners. Next, the function u (x) is defined as the cardinality of the maximum coalition in which x is the winner of the Condorcet.

Then the options with the maximum ux value are selected:

This rule for selection and ranking has a computational complexity of at least quadratic.

25. Simpson's procedure (maximin procedure)

We construct a matrix S + such that ∀ a, b∈X, S + \u003d (n (a, b)), where

n (a, b) \u003d card (i∈N | aP i b), n (a, a) \u003d + ∞.

This rule for selection and ranking has a computational complexity of at least quadratic.

26. Minimax procedure

Let us construct a matrix S such that ∀ a, b∈X, S + \u003d (n (a, b)), n (a, a) \u003d - ∞.

Collective choice is defined as

This rule for selection and ranking has a computational complexity of at least quadratic.

27. Strong q-Pareto simple majority rule

Let f (P →; i; q) \u003d (X∈A- || card (D ↓ i (x)) ≤q) determine q + 1 options from the maximum and lower in the linear order P i. Let ℑ \u003d (I⊂N- || card (I) \u003d) (where the function [χ] denotes the smallest integer greater than or equal to x) be a family of prime majority coalitions. Let us introduce a function that chooses an option that is among the upper options for each voter in at least one coalition of a simple majority, and start with q \u003d 0. If there is no such option for q \u003d 0, then the choice over coalitions of the simple majority with q increased by one (i.e., the weight q \u003d 1), etc., is re-examined, until the choice is empty. From this non-empty set, the option with the smallest number is selected, which is accepted as a collective choice.

This selection and ranking rule has exponential computational complexity.

28. Strong q-Pareto majority rule

This rule is similar to rule 26, with the addition that if several options are selected, then for each of them the number of coalitions that have chosen it is calculated. Then the options with the maximum value of this indicator are selected.

Options with the maximum value of this indicator are selected. This selection and ranking rule has exponential computational complexity.

29. Strongest q-Pareto simple majority rule

We introduce the function

C (A) \u003d ∩ I ∈ ℑ f (P →; I; q)

where f (P →; I; q) \u003d (χ ∈ A - | | card (∩ ↓ i (x)]) ≤ q), card (I) \u003d [n / 2] is a function that chooses a variant, Pareto optimal in every coalition of simple majority, and start with q \u003d 0. If there are no such elements, then the case q \u003d 1, q \u003d 2, etc. is considered, until the choice is empty. From this non-empty set, the option with the smallest number is selected, which is taken as a collective choice. This selection and ranking rule has exponential computational complexity.

30. Rule of suprathreshold selection

Let the criterion φ (x), φ: A → R 1, be given on the set A, and the threshold function V: 2 A → R 1 on the set 2 A, which assigns to each set Xe2A the threshold level V (X).

The suprathreshold selection rule is presented as the following expression:

n ¯ s t: y ∈ C (X) ⇔ (y ∈ X & ϕ (y) ≥ V (X)).

This selection rule has a linear computational complexity; for ranking, the computational complexity depends on the input data, in the worst case, no more than quadratic.

1. A method for selecting and ranking effective search results options, which consists in the fact that the criteria for assessing the relevance of a search result option to a search query are preliminarily formed and a finite number of search results options or a set of procedures for selecting and ranking search results options and the sequence of their execution for selecting the results the search, assessed as the most effective, evaluate each of the search results options according to their relevance to the search query criteria, on the basis of which the search results options are ranked by assigning a rank to each of them from the condition of meeting the largest number of criteria in descending order; the selection and ranking of search results variants are sequentially carried out by the superposition method in at least two stages, if the number of search results variants in the remaining group of search results variants corresponds to a predetermined finite number of search results variants for selection or all specified selection procedures are used, selection of search result variants and their ranking is stopped and the search result options from the selected group are evaluated as the most effective, if the number of search results options in the remaining group of search result options does not correspond to a predetermined finite number of search result options for selection, the selection of search results and their ranking continues, while selection of search results options, their ranking and exclusion are carried out until a specified number of search result options is reached or until all specified procedures are used in The selection and the selected group of options are rated as the most effective.

2. The method according to claim 1, characterized in that at the first stage the search results are selected in the presence of a large number of them by the superposition method using selection and ranking methods characterized by linear computational complexity O (n), and the group of search results is excluded that have the lowest rank.

3. The method according to claim 1, characterized in that at the second and subsequent stages, the criteria for evaluating the search query are formed, on the basis of which the variants of the search results are ranked and the variants of the search results are selected from the remaining array processed at the previous stage by the superposition method using the methods, the computational complexity of which is not less than quadratic O (n 2) and exclude the next group of search results with a lower rank.

4. A method for selecting and ranking effective variants of search results, which preliminarily formulates criteria for assessing the relevance of a variant of search results to a search query and sets a finite number of variants of search results for selection, assessed as the most effective, evaluates each of the variants of search results by relevance search query criteria, on the basis of which the search results are ranked by assigning a rank to each of them from the condition of meeting the greatest number of criteria in descending order; the selection and ranking of search results variants are sequentially carried out using the superposition method in at least two stages, if the number of search results in the remaining group of search results matches a predetermined finite number of search results for selection, the selection of search results and their ranking is stopped and the variants search results from the selected group are assessed as the most effective, if the number of search results in the remaining group of search results does not correspond to a predetermined finite number of search results for selection, the selection of search results and their ranking continues, while the selection of search results, their ranking and exclusion are carried out until a predetermined number of search results is reached, the selected group of search results is evaluated as the most effective.

5. The method according to claim 4, characterized in that at the first stage, the selection of search results options is carried out in the presence of a large number of them by the superposition method using selection and ranking methods characterized by linear computational complexity O (n), and a group of search result options is excluded that have the lowest rank.

6. The method according to claim 4, characterized in that at the second and subsequent stages, the criteria for evaluating the search query are formed, on the basis of which the variants of the search results are ranked and the variants of the search results are selected from the remaining array processed at the previous stage by the superposition method using the methods, the computational complexity of which is not less than quadratic O (n 2) and exclude the next group of search results with a lower rank.

7. The method according to claim 4, characterized in that a set of procedures for selecting and ranking options for search results and the sequence of their execution are additionally specified.

8. A method for selecting and ranking effective search results options, which consists in the fact that criteria for assessing the relevance of a search result option to a search query are preliminarily formed and a set of procedures for selecting and ranking search results options and the sequence of their execution for selecting search results options evaluated as the most effective are set evaluating each of the search results options according to their relevance to the search query criteria, on the basis of which the search results options are ranked by assigning a rank to each of them from the condition of meeting the greatest number of criteria in descending order; the selection and ranking of search results variants are sequentially carried out by the superposition method in at least two stages, the selection of search results, their ranking and exclusion are carried out until all the specified selection procedures are used and the selected group of search results is evaluated as the most effective.

9. The method according to claim 8, characterized in that at the first stage, the search results are selected in the presence of a large number of them by the superposition method using selection and ranking methods characterized by linear computational complexity O (n), and the group of search results is excluded that have the lowest rank.

10. The method according to claim 8, characterized in that at the second and subsequent stages, criteria for evaluating the search query are formed, on the basis of which the variants of the search results are ranked and the variants of the search results are selected from the remaining array processed at the previous stage by the superposition method using the methods, the computational complexity of which is not less than quadratic O (n 2) and exclude the next group of search results with a lower rank.

11. The method according to claim 8, characterized in that, additionally, a finite number of variants of the search results are specified for the selection, evaluated as the most effective.

12. The method according to claim 8, characterized in that in order to select the most effective group of search results options, additional selection and ranking methods and the sequence of their execution are set, and the selection and ranking are repeated.

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Alexander Levkin

General Director of the Patent Bureau "Tsarskaya Privilege".

For an innovative idea to become capital, it must be successfully launched into the market. For this, it is not enough to create a product; it is important to take care of the protection of intellectual property and effectively patent the development.

A well-executed patent is a legal monopoly, a tool for capitalizing a company and attracting business investment. However, often inventors, when filing a patent, try to keep the details of the technology secret, fearing theft of ideas. This leads to a narrowing of the scope of rights and a decrease in the resistance of the patent to challenge. To protect yourself from mistakes, it is worth knowing about the nuances of the process.

Publicity risks

First, you need to understand how the patenting procedure itself goes. On behalf of the inventor or a legal entity, a package of application documents is submitted to the Federal Institute of Industrial Property (FIPS). It includes:

• patent formula (essence of the invention in one sentence);
• a detailed description that explains the details;
• essay;
• application for registration of a patent.

Also, drawings and other documents that reveal the idea in more detail may be attached to the application.

The package is submitted to the FIPS, and after one to one and a half years, information about the invention is published on the department's website.

It is at this stage - after the publication of the development description - that the innovator faces risks.

On the one hand, the patent applicant must compose the description in such detail and clear that an abstract specialist in the relevant field of technology could reproduce the invention and obtain the claimed technical result. Otherwise, the owner of the idea risks receiving a refusal from the FIPS for patenting.

On the other hand, the patent publication will be available to everyone, which means that anyone can reproduce the invention. From the point of view of legislation, the patent holder has the right to protect his idea from illegal use, but it is very difficult to track infringers and fight them. Therefore, it is necessary to describe your development in a balanced way.

How to obtain the rights to an invention and maintain a competitive advantage

Method 1. To classify some of the information as know-how

How to implement such a security strategy? When filing a patent application, you can keep some of the information secret or, as they say, as know-how.

According to the Civil Code of the Russian Federation, know-how (secret of production) is information of any nature that has actual or potential commercial value due to its unknown to third parties. Third parties should not have free access to such information on a legal basis, and the owner of such information is obliged to take reasonable measures to maintain their confidentiality, including by introducing a trade secret regime.

Example. The innovator first came up with the idea of \u200b\u200busing nickel slag as aquarium soil. In this case, it is enough to indicate general information about the composition of the slag, the technology of its production and purification, allowing it to be used for its intended purpose, or just an example of the invention. At the same time, it is possible to introduce a commercial secret or confidentiality regime at the enterprise and formalize as know-how the features of the processes of cleaning and preparing the slag, which determine its highest consumer characteristics.

This strategy is more suitable for patenting applications and methods based on new principles.

Then the general essence is reflected in the patent, and the detailed and most important information remains confidential, while the company's employees are responsible for ensuring that the information does not go into the wrong hands. As a result, a potential competitor who will like the patent will have to spend a lot of time and resources on their own research, and the creator of the idea by that time can bring his product to a new level of quality.

Method 2. Disclose information about all possible and impossible embodiments of the invention

As paradoxical as it may sound, the inclusion of a large amount of information in the description can reliably protect against illegal use of the idea. When submitting documents to FIPS, there is the possibility of one interesting maneuver - providing the maximum number of options for implementing the invention.

For example, in a patent description, you can set out the best, worst, and even nonexistent options for your design. This will help to obtain the greatest amount of rights and at the same time protect valuable information by hiding it in lengthy wording.

The overall picture is significantly blurred due to the many options, and it will be more difficult for competitors to find out which of the declared is the most effective.

The owner of the idea will play into the hands of the use of so-called hyperonyms, or generic concepts. We are talking about the broadest possible formulations of individual features of an idea.

Example. The creator of the double distillation distillation unit does not need to indicate in the formula a specific embodiment of the apparatus. The idea can be defined as follows: "The distiller contains two series-connected stills, one of which is located inside the other." In this case, a large number of drawings can be attached to the description with various options for placing and connecting the distillation stills, among which there will be the best.

This strategy is primarily relevant when patenting devices, when it is extremely difficult to keep secret design features, since they can be determined through product reengineering. Blurring the description will disperse the focus of attention of potential counterfeit manufacturers at least until the moment of large-scale production of products, due to which the copyright holder will again be one step ahead.

Method 3. Designate the range of application and classify important

If we are talking about the patenting of substances, methods of their production or other technological aspects, then, as a rule, when patenting, the claims include information on various technological modes or on the chemical composition of substances. Such information should be presented in the form of ranges.

Inventors who use this technique incorrectly run the risk of being left without a patent even after registering it. The fact is that often, when using ranges, the inventor indicates them at random or expands them to such an extent that the solution stops working. At the same time, few people know about the possibility of challenging a patent on the basis of the criterion of "industrial applicability", when a patent is declared invalid if its formula and description do not allow obtaining the claimed technical result. How to specify ranges correctly?

It is necessary to experimentally determine the upper and lower boundaries of each parameter, that is, to find out at what maximum and minimum characteristics the technology remains operational.

Example. Scientists have invented a substance for water purification from oil based on polysaccharide microgels. The concentration of microgels in water should be between 0.1 and 20 grams per liter for the process to have the desired result. At a lower concentration, microgels will not capture oil at all, and at a higher concentration, the substance will immediately precipitate.

In this case, in the description of the patent, it is necessary to give examples indicating the technical result when the concentration of microgels of polysaccharides will be within these limits. One or more examples should be added indicating the concentration within this range. It is also worth providing a rationale for why the technical result is not achieved outside the specified range.

With this approach, the innovator, on the one hand, provides reliable information about the technical solution, which means that he eliminates the risks of refusal to register and contest a patent. On the other hand, it does not disclose and can classify as know-how the most effective way to implement its idea. The inventor is buying time again as competitors go through a million combinations of different parameters in search of the most effective options.

Outcome

The considered tools can improve the efficiency of patenting, reduce or eliminate some risks, but they are not a guarantee of protection. It is necessary to take a comprehensive approach to the processes of intellectual property management in each individual case, taking into account the specifics of development, copyright holder, technology, competitors and much more.

It is important that the inventor understands the need to be open and honest with the patent specialist. You should provide comprehensive information, immediately pointing out the places where the know-how is contained, and talk about all embodiments of the invention. By providing false information, the inventor runs the risk of being left with an invalid patent.

The best and most effective use of the immovable object is the option of using a free or built-up plot of land, which is legally possible and properly formalized, physically feasible, provided with appropriate financial resources and gives the maximum value.

Usually the analysis of the most effective use is carried out according to several alternative options and includes the following areas:

Market analysis;

Analysis of the feasibility of the option;

Analysis of the most effective use.

Market analysis involves identifying the demand for alternative use cases in order to study supply and demand, market capacity, dynamics of rental rates, etc. for each option.

A feasibility study involves calculating the basic components of cost: income stream and capitalization rates to determine the cost, taking into account the variables of each legally sound and physically feasible option.

The analysis of the most effective use involves the development of a detailed plan for the implementation of each option with consideration of specific market participants, the timing of the project, sources of funding for choosing an option that ensures the maximum productivity of the evaluated object.

Analysis criteria for the most effective use:

Legal admissibility;

Physical feasibility;

Financial security;

Maximum productivity.

The validation of the legal admissibility of each considered use case is carried out in all cases first. The choice of the most efficient use of real estate can be influenced by the existence of long-term lease agreements. During the remaining lease term, the use of the property depends on the terms of the lease. If the most efficient use of the property is constrained by the existence of a lease, this should be reflected in the valuation report.

Example. If the object is limited by a land lease that expires in more than 12 years, then there may be no economic feasibility in constructing a new building that has an economic life of 40 years.

Example. Construction of buildings of a certain number of storeys, fire breaks, insolation requirements.

Physical feasibility. The criteria for physical feasibility - size, shape, area, design, ground condition and access roads to the site, and the risk of natural disasters (such as floods or earthquakes) - affect the intended use of the land.

Financial security. An option is considered financially viable if it provides operating income equal to or greater than operating costs, financing costs, and the required capital recovery scheme. If the type of use does not imply the receipt of a regular income from operation, then during the analysis those options are selected that create real estate, at a cost equal to or greater than the cost of construction or reconstruction of the facility for this new type of use. The appraiser must compare the capital gains or income from the use of the property with the capital expenditures incurred. If the income is lower than the costs or exceeds them only slightly, this type of use is recognized as financially unfeasible.

To assess the uses that generate regular operating income, for each of them the appraiser calculates the total net operating income, the individual rate of return on invested capital, the amount of income attributable to land. If the net income corresponds to the required return on investment and provides the required yield on the land, this type of use is financially feasible.

Maximum productivity is the highest cost of a land plot as such, regardless of whether it is vacant (actually or conditionally) or built-up. Thus, the implementation of this criterion presupposes, out of all legally permitted, physically realizable and providing a positive income, the choice of the type of use that provides the maximum cost of the basis of real estate - a land plot.

The maximum productivity of a land plot is determined by correlating the amount of its income with the capitalization rate required by the market for this type of use. The type of use that provides the most profitable land is the most efficient. At the heart of all the methods used to determine the value of a land plot in order to select the most effective option is the so-called remainder technique.

Income from land is considered as the balance between the aggregate income generated by real estate and those amounts of income that are provided by attracting labor, capital, fixed assets (functioning buildings and structures). The cost of a land plot, in turn, represents the difference between the total cost of the entire property and the residual value of buildings or the cost of their construction.

The way to make the best use of real estate can either be achieved on the basis of existing buildings, or assume the construction of fundamentally new improvements, which requires considering the land plot as free.

Based on this, appraisers apply two techniques when analyzing the best use of real estate:

- the most efficient use of the site as undeveloped;

- the most efficient use of the site as built-up.

The method of determining the best and most effective use of the appraised real estate as an undeveloped land plot is based on the assumption that it has no buildings, or can be freed from buildings as a result of their demolition. As a result, the value of land is determined based on the choice of possible use cases that ensure the profitability of real estate, and underselection of parameters of real estate objects in accordance with a specific purpose.

The option of using a plot of land as undeveloped has two main types:

The use of a plot of land for speculation, that is, for selling it without improvement to an investor, who will subsequently develop it in accordance with the requirements of the market or his own preferences. This option is applicable in
the case when real estate markets are oversaturated.

Development of a land plot with new buildings and structures, including:

- development without intermediate use, if a new use option is being considered that is accepted by the market at the date of analysis;

- development with intermediate use presupposes the temporary preservation of the existing use option until the new option is demanded by the market, based on the forecast of the market situation;

- division or unification of a land plot to achieve the most efficient use;

- development of the site with new buildings, similar in purpose and physical parameters to the existing object.

Acceptance of the most effective use of a land plot as built-up involves the preservation of existing buildings on the analyzed plot.

The option of using a plot of land as built-up has two main types:

- preservation of the existing purpose of the appraised real estate;

- change of the existing purpose of the appraised real estate.

Evaluation of maximum productivity, depending on the assessment of the capitalization ratio, is carried out using the following methods.

First method: The land plot is considered undeveloped, capitalization ratios for land and buildings are different.

1. Determination of the cost of building a conditionally free land plot with buildings and structures of a certain purpose, taking into account market demand and supply.

Corrections taking into account the load factor and losses during collection of payments.

Determination of the possibility of obtaining and the amount of other income.

6. Calculation of operating costs.

7. Calculation of the reserve for capital expenditures.

8. Calculation of net operating income.

9. Calculation of the capitalization ratio for buildings.

10. Evaluation of the income generated by the constructed buildings and facilities.

11. Calculation of income attributable to land.

12. Calculation of the capitalization ratio for a land plot.

13. Evaluation of the value of a land plot by capitalization of income brought by land.

Method two: Land plot is considered undeveloped, capitalization ratios for buildings and land are the same.

Determination of the cost of building a conditionally free land plot with buildings and structures for a specific purpose, taking into account market demand and supply.

Calculation of potential gross income.

Making adjustments taking into account the load factor and losses during collection of payments and the amount of other income.

Estimation of actual gross income.

Calculation of operating costs and capital cost reserve.

Calculation of total net operating income.

Calculation of the total capitalization ratio for the appraised property.

Real estate appraisal by capitalization of net operating income generated by real estate.

Estimating the value of the land income as the difference between the estimated value of the property and the cost of improvements.

Third method: The land plot is considered to be undeveloped, and the market price of the sale of the property for the intended purpose is known:

1. The market value of a finished real estate object for a specific purpose, which can be built on the analyzed land plot, is determined.

2. The cost of construction is calculated, including the developer's profit.

3. The cost of a land plot is assessed as the difference between
the sale price of the property and the total costs.

Fourth method: The land plot is considered as built-up, the buildings require some improvements:

Determination of the general capitalization ratio.

Calculation of the cost of improving the facility.

Calculation of the increase in the value of real estate, taking into account the improvements made.

Fifth method: The land plot is considered as built-up, which does not require restructuring:

Calculation of net operating income generated by real estate.

1. Determination of the general capitalization ratio.

Real estate appraisal by capitalization of net operating income.

The identified features of real estate objects and the development of the market situation may require non-standard uses.

Standalone uses

As a rule, the most effective options for using the analyzed real estate do not differ from the use of similar objects. However, due to the unusualness or uniqueness of the assessed object, its most effective use may differ.

Intermediate uses

If the option for the most efficient use of the property is based on changes in the market situation in the future and, therefore, can be implemented over time, the use case that has developed at the date of valuation is considered as an intermediate one. An intermediate use, which may change over time, can also be identified as the most effective option for a given period.

Legally conflicting uses

If the actual use of the object, permitted by law, does not comply with the standards in force in the area of \u200b\u200bits location. This is usually a consequence of a change or the emergence of new zoning norms.

Uses that are not the most effective

In practice, real-life buildings may not correspond to the most effective way of using the plots on which they are located. A change in the situation may require both a change in the existing purpose of real estate and its preservation, but on a qualitatively different basis, requiring certain capital expenditures.

Multidisciplinary uses

Thus, a large building can provide residential premises, offices, shops, service centers, etc. Similarly, housing, shopping and entertainment centers and other infrastructure facilities can be built on a land plot.

Special-purpose uses

For example, the most efficient use of a plant that produces equipment for heavy engineering is likely to be continued production of this equipment, and the most efficient use of a grain elevator is likely to continue to be used as an elevator.

Speculative uses

The owned land plot intended for sale in the future is considered a speculative investment instrument.

Excess and excess land area

Built-up areas may have excess area not required by the current use of buildings. Undeveloped plots may have an area that is not required for the main most effective use. The most effective way to use excess areas of the site can be the development of additional buildings or keeping them undeveloped.

In certain cases, additional space that is not needed for existing buildings and cannot be separated from the object and sold, is an extra space.

Property valuation with an income approach

Basic concepts

Waiting principle

Estimating market value using the income approach is based on the conversion of income that the asset being valued is expected to generate in the course of the remaining economic life into value. From a theoretical point of view, the source of income can be anything: rent, sale, dividends, profit. The main thing is that it should be a product of the asset being evaluated. With the help of this approach, it is possible and expedient to evaluate those assets that are or can be used in the interests of generating income (real estate, stocks, bonds, bills of exchange, non-tangible assets, etc.).

The basic principles for evaluating an income asset are the expectation principle and the substitution principle. The expectation principle for this approach is the main method-forming principle. It states that the value of the K asset is determined by the current (today's, current) value (PV -from English present value) of all its future incomes I:, where to -the period of ownership of the asset.

The higher the income potential of the assessed asset, the higher its value. In this case, the analysis of income should be carried out throughout the rest of the economic life of the asset under the condition of its use during this period in the most efficient way.

In accordance with the principle of substitution, the maximum value of F of an asset should not exceed the lowest price Va,for which another similar asset with equivalent yield can be acquired:, where t -number of analogues. This principle is analogous to the economic principle of investment alternatives.

Within the framework of the income approach, a distinction is made between the direct capitalization method and the income capitalization method according to the rate of return on capital (Figure 3.1). These methods are based on the analysis and assessment of net operating income and the capitalization or discounting ratio.

With direct capitalization, the net operating income of the first year of using the asset is estimated, provided that it is at the stage of generating typical income, and the capitalization ratio is estimated to convert the income into the current value, and in the capitalization method at the rate of return on capital, the forecast of the net operating income in the process of using the asset, including net income from reversal at the end of the forecast period, estimation of the discount rate and determination of the amount of the current values \u200b\u200bof these incomes.

Figure 3.1 - Classification of assessment methods by income.

These methods differ in the ways of analyzing and constructing the stream of income and the coefficients of their transformation into present value. In the direct capitalization method, for assessing the market value, the net income of the first year from the use of an asset is divided by the capitalization ratio, obtained based on the analysis of data on the capitalization ratio of asset income, similar to the asset being valued. At the same time, there is no need to assess the trend of changes in income over time, and when assessing the capitalization coefficient - to take into account its components separately: the rate of return on capital and the rate of its return.

It is assumed that the accounting for trends in all components of the assessed asset is embedded in market data. It should be noted that the direct capitalization method is applicable to the valuation of existing assets that are used in the most efficient way and do not require at the date of valuation of long-term capital investments in repair or reconstruction. When assessing the capitalization method according to the rate of return on capital, the trend of changes in net income over time is separately taken into account and all components of the capitalization ratio are analyzed separately.

Direct capitalization method is a method for assessing the market value of an earning asset based on direct conversion of the most typical first year income into value by dividing it by the capitalization ratio, obtained based on an analysis of market data on the ratio of income to asset value, similar to the one being estimated.

The capitalization method at the rate of return on capital is a method for assessing the market value of an earning asset based on the conversion of all cash flows that it generates in the course of the remaining economic life into value by discounting them at the valuation date using the rate of return on capital, extracted from the market with alternative investments in terms of risk.

The capitalization method according to the rate of return on capital, in turn, can have two varieties from a formal (mathematical) point of view: the method of discounted cash flow analysis (CP analysis) and the method of capitalization according to calculation models.

The method of analysis of discounted cash flows is the method of capitalization at the rate of return on capital, in which, to estimate the market value using the rate of return on capital as the discount rate, the cash flows of each year of operation of the asset being assessed are separately discounted with the following summation including cash flow from its re-sale at the end of the holding period.

Method of capitalization according to calculated models - the method of capitalization according to the rate of return on capital, in which, in order to assess the market value, the most typical income of the first year is converted into value using formalized calculation models of income and value obtained on the basis of an analysis of their trends in the future ...

The net operating income that an asset generates is the difference between the actual gross income and operating expenses.

In general, in accordance with the expectation principle, the mathematical expression for assessing the market value of an asset using the income approach is as follows:

where V o -market value assessment, q -current period number, I q -net operating income q somethingperiod, Y—rate of return on capital (income discount rate), V P- cash flow from reversion, to- number of the last period of ownership (When evaluating a property, the forecast period is considered as the period of ownership.)

In a real estate object, the non-depreciable part is the land plot, and the depreciable part is the improvement of the land plot. The land plot as a part of the Earth's surface is not subject to wear and tear, i.e. from an economic point of view, a land plot should be considered as an endless (inexhaustible) source of income, the value of which can only increase over time. Improvements have a finite economic life - a period of time during which the amount of income generated by the facility exceeds the amount of expenses for its operation A depreciable asset should also include an investment aimed at acquiring the right to lease an asset over a finite period of time.

Thus, the income I q (from the English word - Income) of some q-th year can be divided into two components:

where is the return on investment (return on capital) and is the return on the initial investment (return on capital).

Investment income for the qth year, in turn, can also be divided into two components: investment income, equal to the market value of improvements at the beginning of the qth year, and investment income, equal to the market value of the land plot in the same year :

The rate of return on capital invested in land is equal to the rate of return on capital invested in improvements: Y L \u003d Y B \u003d Y.

Therefore, the return on capital can be represented as the product of the value of this capital by a single rate of return:

- from improvements

From (6.1.2) it follows that the return on capital attributable to improvements and the current market value are related to each other by a directly proportional relationship 1. In this case, income is positioned at the end of the year, and the cost of improvements - at the end of the previous year or at the beginning of the current one. Improvements due to natural wear and tear lose their value. Therefore, the income associated with improvements is also a diminishing function of time.

For objects requiring certain capital investments for their improvement (free land plot, "unfinished", reconstructed object, etc.), the initial investment from an economic point of view should be defined as the amount of unrecovered investments V HU, i.e. ... the future value of the flow of capital investments (expenses) for the creation of an object as a source of income or, which is the same, accumulated by the date of exploitation of a profitable asset at a certain percentage rate of the amount of costs for its creation

The search for a solution to this problem is in the answers to two questions:

How willing the market is to accept (support) the intended use case;
- what are the costs and financial feasibility of development. One of the ways to answer is to analyze the NEI of the earth.

Of all the factors affecting, judgment about the most effective use of the property is the most important. This judgment is based on a comprehensive analysis of the area, microdistrict, site and options for its development.

The entire process of assessing the market value of a property is then built on the assumption of the most efficient use. This analysis becomes the heart of the valuation problem, requiring time, effort and the application of the professional skills of the valuer.

Necessity and essence of NEI analysis

The analysis of the most effective use of the real estate object involves a detailed study of the market situation, the characteristics of the object being evaluated, the identification of options demanded by the market that are compatible with the parameters of the evaluated object, the calculation of the profitability of each option and the assessment of the value of real estate for each use case. Thus, the final conclusion on the most effective use case can only be made after calculating the cost.

The most effective use of a real estate object is determined by the NEI principle and represents an option for the use of a free or built-up plot of land, which is legally possible and properly formalized, physically feasible, provided with appropriate financial resources and gives the maximum value.

The optimal use of a plot of land is determined by the competing factors of the specific market to which the property being valued belongs, and is not the result of subjective speculation by the owner, developer or appraiser. Therefore, the analysis and selection of the most effective use is, in fact, an economic study of market factors that are significant for the evaluated object.

Market factors used to formulate a conclusion on the most efficient use of real estate at the date of valuation are considered in the general data set collected and analyzed to determine the value of the property. Therefore, the identification of the most effective use for a particular property can be qualified as the basis for calculating its market value.

If the property being appraised assumes subsequent personal use or lease, then their main motivation in calculating the cost will be reduced to the received consumer qualities of the object (income, prestige, privacy, etc.). Investment motivation, in addition to the amount of income received and capital accumulation, takes into account such parameters as tax incentives, project feasibility.

Usually, the analysis of the most effective use is carried out according to several alternative options and includes the following areas:

Market analysis;
- analysis of the feasibility of each option;
- development of a detailed plan for the implementation of each option.

Market analysis involves identifying the demand for alternative use cases in order to study supply and demand, market capacity, dynamics of rental rates, etc. for each option. The optimal combination of factors leading to the greatest cost is the most efficient use.

Feasibility analysis involves calculating the basic components of value - income stream and capitalization rates to determine the cost, taking into account the variables of each legally justified and physically feasible option.

The analysis of the most effective use implies the development of a detailed plan for the implementation of each option with consideration of specific market participants, the timing of the project, sources of financing for choosing the option that ensures the maximum productivity of the evaluated object, and provides for a comparison of all possible options for building the site. The residual value of the land (plot) is calculated for each option.

The highest residual value of land corresponds to its most efficient use.

The customer can specifically specify his interest in a full-scale study of the most effective use of the evaluated object.

Determinants of NEI

1. Potential of location. Due to the uniqueness and invariability of the topographic position of a plot of land, location is the main factor that determines its value. In the US, appraisers say there are three main factors that affect the value of a property - location, location, and location. It is a responsible task for the appraiser to identify the most profitable use of the site.

In determining the location of the site, one should consider:

How does it compare with the type of land use prevailing in a particular area;
- its availability.

The potential for the location of the same site, depending on the land use option, can be either high or rather low.

2. Resource quality of the site. The study of this issue makes it possible to determine the potential of the physical qualities of the territory, i.e., those possibilities that can be realized during the development of the site. The resource quality of the site may allow an appraiser to recommend the construction of a ten-story, five-star hotel, warehouse complex or waste processing facility on it. In order to make a decision, the appraiser must find out all the restrictions on the various development options related to both topography and soil composition (susceptibility to flooding, water table, etc.), as well as zoning and local restrictions. The resource quality of the site, its resource potential also depends on the adjacent land use, the prospects of the region and the microdistrict. This, of course, also depends on the situation in the country - the situation and the prospects for its development may induce the appraiser to recommend building a bunker that can withstand a direct hit of an atomic bomb, and not a glass-aluminum five-star hotel, as an optimal use of the site.

3. Market demand. To develop the concept of the most effective use, the most important is the analysis of market behavior. The market, combining supply and demand, creates market value. When the task of assessment is to determine the market value, the analysis of NEI allows you to identify the most profitable and most competitive use of the assessed object.

In addition to considering the obvious general questions of demand - supply in the market, the target market is determined, those users who can buy or rent this property.

The infrastructure of the land plot itself and the surrounding areas (the degree of development of the road network, the intensity of traffic and pedestrian flows, the presence of railway and access roads, the distance from shopping centers) is considered to study the economic location of the site - its situation. This concept also includes an analysis of the demographic situation in the area in which the land plot is located (age composition of the population, its ability to pay), possible competitors and competing objects, etc. The analysis identifies and evaluates their convenience and other characteristics. Competing objects increase supply and can divert some of the demand to themselves. In addition, it is important to identify competing properties under construction and design that will compete with the property being evaluated in the future.

After determining the target market, the analysis of the situation allows you to identify additional amenities that can provide a competitive differential between the property being evaluated and those offered on the real estate market. The competitive differential is the added quality that gives the property a comparative advantage. ("And from our window Red Square is visible! And from your window only the street is a little bit ...") Sauna, storage rooms, workshops, a gym, a garage in the basement, a solarium on the roof, fireplaces in apartments can act as a competitive differential of a residential building , loggias, picturesque views from the windows, guarded parking lot, etc.

Thus, based on market analysis, the following are determined:

A) target market (potential users);
b) existing competing objects;
c) competing objects under construction and projected;
d) competitive differential.

4. Technological and financial feasibility. The technological feasibility of building a land plot consists in answering the question whether it is possible to carry out the planned construction option within a given time frame with an appropriate financing schedule and a construction and installation work organization (CMP) project. The limiting conditions of the project are the number of necessary qualified workers and managers, the provision of building materials and equipment, as well as safety standards for construction and installation work, fire safety, sanitary and epidemiological supervision, etc.

Thus, the issue of the sufficiency and availability of financial, time, labor and other attracted resources must be resolved. Insufficient qualifications of construction workers, the absence or unreasonably high price of the necessary finishing materials, the impossibility of organizing the required flow of payments (credit line), etc. - all this can cause the technological insolvency of the project of a particular building.

Of course, the project itself may be unrealistic - be it the Tower of Babel or the Palace of Soviets of the USSR (I mean the competition projects of 1931-1932 and the preparation of the foundation pit).

When considering the proposed investment project for the considered use case, financial feasibility is one of the main factors in the implementation of the NEI principle of a land plot. At this stage, the tasks of financing a project in real estate are solved, cash flows and discount rates are determined that satisfy the investor's requirements. Particular attention is paid to the time of receipt and outflow of funds, the cost of operating equipment, debt service payments, proceeds from the sale of the object and refinancing of funds.

Thus, when deciding on the NEI of an object, it is necessary to analyze the following main factors:

1) location potential;
2) resource quality of the site;
3) market demand;
4) technological and financial feasibility.

The first two are land oriented and the last two are improvement.

NEI criteria

The variant of the most efficient use of the appraised real estate must meet four criteria:

1) legal admissibility;
2) physical feasibility;
3) financial justification;
4) maximum productivity.

The sequence of consideration of these criteria in the course of analyzing various options for the use of real estate in Russian appraisal practice usually corresponds to the above. This sequence of the analysis procedure is due to the fact that the most effective use case, even with the necessary funding, is not feasible if it is legally prohibited or its physical implementation is impossible.

Legal admissibility

The legal justification for the development of a land plot lies in its examination from the point of view of current legislation, urban planning standards (zoning, environmental protection, protection of historical buildings, monuments, fire safety, energy consumption, etc.), promising solutions for the district planning of the site, restrictions of the local administration and the demands of the local population. The appraiser also considers environmental legislation, building codes and regulations, private restrictions.

The choice of the most efficient use of real estate can be influenced by the existence of long-term lease agreements. During the remaining lease term, the use of the property depends on the terms of the lease. If the most efficient use of the property is constrained by the existence of a lease, then this factor should be reflected in the valuation report. For example, if a property is limited by a land lease that expires in more than 12 years, then it may not be economically viable to construct a new building that has an economic life of 40 years.

In addition, it is necessary to take into account possible restrictions that may be included in the contract for the acquisition of real estate. Restrictions may relate to some areas of use, specify the location of buildings on a land plot, parameters of buildings, the type of building materials used. If restrictions on the title deed conflict with more general legal regulations, such as building codes and regulations, then the strongest legal restriction is usually taken into account.

Building codes can constrain development with the most efficient structures, increasing building compliance costs. This ultimately hinders the development of territories. In some areas, building codes are used to reduce new construction and restrict growth.

The appraiser must familiarize himself with all the restrictions associated with the zoning of the territory on which the object is located (by the type of development, its density, the height of buildings and structures; protection of historical and architectural monuments; permitted building materials and technologies, etc.).

The current land use rules are aimed at protecting the environment. Appraisers should take into account air and water purity standards, as well as public opinion regarding proposed development projects. For example, for the construction of buildings of a certain number of storeys, fire breaks. Insolation requirements.

Situations are possible when the current restrictions do not allow implementing the use that, according to the evaluator's calculations, will be optimal. But the appraiser may have sufficient grounds to count on the introduction of amendments to the normative acts that will allow the option that he considers to be optimal.

Having substantiated the reasonableness and likelihood of these changes, the appraiser is entitled to include this notional best use case in the report. For example:

A) the assumption about the transfer of agricultural land for residential development;
b) the assumption about the inclusion in the future of the houses of monuments in the market turnover, etc.

However, the possibility of changing legislation, building codes and zoning rules is never fully determined.

Physical feasibility

Physical, soil and landscape capabilities are important factors for the analysis of the NEI of a land plot. For new buildings, the size, shape and its natural features, vegetation are determined, topographic surveys are carried out, and the depth of water is measured. For old building sites such information is usually already available and must be found. These data are necessary to decide what kind of building, number of storeys and sizes can be built on a specific land plot. Neglecting this analysis is fraught with structural collapses and man-made disasters.

The size of the site, its shape (non-rectangular is more expensive to develop and more inconvenient to use), frontality and depth, access and other factors should be favorable for building. For example, if a built-in space of 10 x 50 m is used as a store, its market value will be influenced by its location along the front - how many - 10 or 50 m - falls on the display part, past which the flow of pedestrians - potential buyers - moves.

Thus, the ultimate usefulness of a land plot depends on its size and shape. Some options are most effective only when using a specific size area. In this case, it is necessary to determine the possibility of expanding the existing land plot. The shape of the plot affects the final productivity, since the costs of building an irregularly shaped land plot can be higher, which further reduces their usefulness compared to other plots.

The same goes for object access. The presence of access roads to the site and utilities increases its final productivity, since savings on its development are achieved. For example, the available capacity of a wastewater treatment plant limits the physical size of the proposed efficient development option.

The physical feasibility of the project is influenced by both the state of the soil and the risk of natural disasters (earthquakes, flooding, floods, floods, etc.). The well-known decision “the city will be laid here in spite of an arrogant neighbor” was political, voluntaristic and had obvious drawbacks - the territory's susceptibility to floods, the state of the soil did not allow us to consider Peter's glorious deed as an example of an impeccable conclusion on the criterion of “physical ability”.

Thus, the topographic or soil characteristics of the land plot are reflected in the functional usefulness of the site. When analyzing a use case for a site, you should consider the various inconveniences and negative aspects that come with this option and map them to the site layout. These moments may include the facts of environmental problems (toxic pollution) in the region.

Some sites achieve their best use only in conjunction with neighboring ones; the appraiser must identify and calculate this. For example, a suburban plot of 6 acres in a particularly prestigious location may reach the highest market value if it is interlocked with neighboring ones and used for the construction of a three-storey mansion, which is clearly "cramped" on 6 acres, which is more likely to correspond to a panel garden house. In the principles of real estate valuation, this situation is described by the principles of balance and economic size. Balance sets the values \u200b\u200bof production factors that are optimal for a certain type of land use, which, in combination, maximize the value of the land; economic size determines the amount of land that is needed to ensure the optimal scale of land use in accordance with the market conditions at that location.

In the process of analyzing the physical feasibility of an effective use case, it is necessary to consider the condition of buildings and structures to determine the possibility of their further operation on a new basis. If buildings need to be rescheduled to ensure optimal use, the costs involved should be calculated and compared with the final return. Typically, the cost of renovating a property depends on the physical condition and location of the property.

Information about a land plot can be obtained from city and regional land committees and commissions, as well as from BTI and appraisal firms. Currently, this information is being systematized and the formation of the state real estate cadastre of the Russian Federation has begun, which considers the land plot and its improvements as a single real estate object.

Financial soundness

An option is considered financially viable if it provides operating income equal to or greater than operating costs, financing costs, and the Required Return on Capital Scheme. Thus, all uses that could generate positive returns are considered financially feasible.

The conducted analysis of the market opportunities to accept a certain option for the use of a land plot will determine how this or that option for its use "reasonably fits" into the nature of supply and demand in the market. The negative aspects identified by the appraiser at the previous stage complicate the development of the site or increase the development costs.

Since all parcels on the market compete with each other, the assessed parcel may not be suitable for the most efficient use if it is inferior to other parcels that are typical for a particular area.

If the type of use does not imply the receipt of regular income from operation, then in the course of the analysis those options are selected that create real estate, at a cost equal to or greater than the cost of construction or reconstruction of the facility for this type of use. The appraiser must compare the capital gains or income from the use of the property against the capital expenditures incurred. If the income is below the costs or exceeds them only slightly, then this type of use is recognized as unfeasible financially.

To assess the uses that generate regular operating income, for each of them the evaluator calculates the total net operating income, the individual rate of return on capital invested, the amount of income attributable to land. If the net income corresponds to the required return on investment and provides the required yield of the land plot, then this type of use is financially feasible.

All legally valid and physically feasible use cases where the return is greater than the cost are considered economically viable.

However, as market conditions change, economically viable use may become unjustified in the future and vice versa.

Maximum productivity

The potential for the most efficient use of land reflects a long-term, carefully designed and rather specific land use program associated with the normal life of buildings and structures. The service life depends on the type of building, the quality of construction work and other factors.

The maximum productivity of a land plot is determined by correlating the amount of its income with the capitalization rate required by the market for this type of use. However, depending on the selected real estate use case, the method for determining the value of land can be different. The choice of the method depends on the degree of reorientation of the actual purpose of the appraised real estate, the level of risk of the considered option, the required rate of return and the period of capital reimbursement, the timing of the proposed use of real estate.

Does it follow from the NEI analysis that it will be the most profitable of all possible options for the object's functioning? Of the legally legitimate, physically possible and economically justified options, the NEI analysis requires you to choose the one that, all other things being equal, is able to bring the most net income or the largest residual value of land to the area being evaluated.

While the property being evaluated may be most appropriate for a particular use case, the evaluator must carefully analyze the market trends of competing properties, both active and prospective. And here it is important to correctly calculate the return on invested capital with the determination of the risk ratios used in the capitalization of financial flows.

The accepted version should be detailed. Not just a residential building or an office building, but if an office building, how many floors? How many office premises, what area? What is the interior decoration, what equipment? What should be the lease payments, operating expenses? What is the construction cost? That is, a clear targeting to a specific market segment must be determined.

If the NEI is calculated, for example, for a 30-year-old building used as a hotel, then in order to identify the use that brings the maximum income, it is necessary to work out various options and resolve questions about the possible demolition of the building or its further use for its intended purpose, rebuilding, superstructure, construction of an extension, partial demolition, repurposing, change in the nature or intensity of use. Should you reduce a losing restaurant to the size of a cafeteria bar? Sell \u200b\u200b(or buy) an adjacent parking lot?

In practice, the study of the NEI of a land plot consists of comparing various options for its development and choosing the optimal one, i.e. is a comparative analysis of the effectiveness of several hypothetical investment management projects, which is a very laborious and crucial stage in the process of assessing the market value of real estate.