About the need to develop an intelligent information system to evaluate investment project environmental effectiveness

. The evaluation of the efficiency of an investment project implemented in the real economy is impossible without assessing its environmental implications. The justification of investment projects may apply modern specialized software. Such software products do not provide an opportunity to fully automate the preparation of the environmental section of the business plan. The authors believe that it is wise to introduce automation into the development of the environmental section of the investment project business plan through an appropriate intelligent information system (expert system). Processing input data requested by the system with various prompts and explanations, the expert system should form the environmental section of the business plan. The proposed system should play the role of a consultant in the field of environmental legislation. It should offer the user a list of environmental protection measures corresponding to their project. The design and application of the expert system will lead to several positive effects: faster development of project materials, improved quality of planning, reduced number of mistakes, lower cost of assessment, increased confidence in the environmental section of the business plan by third-party participants, increased literacy of users of the expert system in the field of environmental protection


Introduction
Expert systems were the first intelligent information systems with considerable demand since they are designed for practical problems. According to specialists, nowadays expert systems are the most popular intelligent information systems in the world. As Liao S.-H. notes, "… their use is proliferating to many sectors of our social and technological life, where their applications are proving to be critical in the process of decision support and problemsolving" [1].
Expert systems enjoy applications almost in all economic sectors, with investment being one of them. The evaluation of the efficiency of an investment project implemented in the real economy is impossible without assessing its environmental implications, which, in some instances, can be crucial. The process of project environmental efficiency evaluation involves environmental professionals, and expenditures for consulting services, and the formation of the environmental section of the business plan of an investment project can be rather significant. The authors believe that it is wise to introduce automation into the development of the environmental section of the business plan of an investment project, by designing the corresponding expert system.
The purpose of the research paper is to build up a concept of an intelligent information system for assessing the environmental effects of investment projects implemented in the real sector of the economy.

Applications of expert systems
Expert systems, as a separate direction of artificial intelligence theory, had formed by the 1970s [8]. During this period, specialists concluded that the effectiveness of a program in solving intellectual problems depends to a greater extent on the knowledge that it possesses, and not only on the formalisms and inference schemes used. The interest of researchers in the development and application of expert systems has led to the creation of many definitions of the term "expert system", several of which are in Table 1. Table 1. Some definitions of the term of expert system given in the academic literature.

Author(s) Definition Source
Maylawati D. S., Darmalaksana W., Ramdhani M. A. "An expert system is a system that stores a human expert's knowledge in order for the computer to be able to solve problems using that knowledge." [6] Leondes C. T.
"…expert system is a knowledge-based computer system which emulates the decision making ability of a human expert." [5] Tan H. "The expert system is a computer system that emulates the decision-making ability of a human expert, which aims to solve complex problems by reasoning knowledge." [9] Akram M., Rahman I. A., Memon I.
"Expert System is an intelligent computer program which solves the complex problems equivalent to the level of a human expert by using task specific information and inference techniques." [3] Kumar S. P. L.
"Knowledge-based expert system or Expert System (ES) deals with computer programme that possess own decision-making capability to solve a problem of interest. ES concerned with creation of computational system that imitates intelligent behaviour of human expertise. <…> ES system performs actions such as perception, interpretation, reasoning, learning, communication and decision-making in order to arrive at a solution for the given problem." [4] Nugroho A. C.
"Expert systems can be defined as tools for generating information from knowledge. It is capable of acting in accordance with a human reasoning process, giving similar [7]  The analysis of the above definitions gives the following essential features of expert systems (see Figure 1): • expert systems are a sort of intelligent information systems; • expert systems are based on experts' knowledge; • expert systems imitate intelligent behaviour of human expertise; • expert systems are designed to solve complex problems in a certain subject area. Expert systems are one of the directions of applied artificial intelligence. The purpose of expert system research is the development of computer programs that, when solving problems difficult for non-experts, lead to results not inferior in quality and efficiency to solutions obtained by human experts in the given subject area. To name their field, expert system professionals often use the term "knowledge engineering" introduced by the American researcher E. Feigenbaum.
The basic idea of expert systems is that experts' experience, representing vast knowledge related to problem-solving in a certain subject area, is transferred from the person to the computer. This knowledge accumulates in the intelligent information system, and, when required, users resort to it for advice. Expert systems can make conclusions and draw certain inferences. Like human consultants, they not only give advice but also, if necessary, explain the logic behind the answer. Expert systems provide powerful and flexible tools for solving many practical problems that often cannot be solved by other methods.
An expert system can be regarded as a computer system consisting of the following main components [10]: Knowledge Base, Inference Engine and User Interface.
The classifications of expert systems are numerous and differ in terms of the division of many systems into classes. By the organization of the information system and the principles of building a knowledge base for the formation of conclusions and inferences, there are the following categories of expert systems [1]: • systems based on rules; • knowledge-based systems; • neural network systems; • systems based on the use of fuzzy sets; • systems based on object-oriented methodology; • case-based thinking systems; • systems of intelligent agents; • systems using modeling and database methodology. Expert systems offer the following advantages: accessibility; the possibility of using in conditions hostile to humans; consistency of obtained results; the ability to accumulate knowledge from several sources; providing database mining. Expert systems find applications in various fields of human activity with a need for knowledge-based decisionmaking: in production, business, medicine, finance, education, etc. These systems can successfully solve a variety of problems [8]: diagnostics, planning, design, interpretation, prediction (forecasting), management, modeling, reengineering, classification, instruction, control, debugging. As Kumar S. P. L. notes, "from the inception ES system, various developments have been done, which broaden its application to include pattern recognition, automation, computer vision, virtual reality, diagnosis, image processing, nonlinear control, robotics, automated reasoning, data mining, process planning, intelligent agent and control, manufacturing" [4].
We should note that expert systems (as an area of artificial intelligence) are constantly evolving in response to changes in the external environment and strive to meet the increasing requirements for their functional characteristics. For example, today it is vital to develop expert systems to aid COVID-19 diagnostics and treatment. See, for example, [11]. Thus, not only the economic well-being of a certain entity but, in some cases, health and even human life often depend on the efficiency of expert systems.

The feasibility of using expert systems in investment
Thus, expert systems are reliable assistants and consultants in economic decision-making. Investment should be no exception here since it has a tremendous impact on the state and the development of the national economy. The design and implementation of effective investment projects lead to development at all economic levels: macro, regional, and the level of an individual enterprise. Each investment project requires a comprehensive assessment of the results and a good justification of efficiency.
The justification of investment projects may apply modern specialized software, aimed at automating the process of drawing up a business plan. Some examples of such software products, please, see here [12; 13].
Despite all the advantages, such software products do not make it possible to fully automate the process of drawing up a business plan for an investment project and require significant human participation. In particular, they do not provide an opportunity to fully automate the preparation of the environmental section of the business plan.
Practice shows that investment projects, implemented in the real economy, can have a significant impact on the environment, and thus require good assessment of environmental efficiency. The section of the business plan devoted to the environmental aspects of investment project implementation is its significant part, without which the project will not receive approval and support from the government. The Russian Federation is no exception here. All developed countries of the world enjoy well-formed environmental protection legislation, which forces economic entities to pursue a socially responsible policy in the environmental sphere.
As a rule, the environmental section of the business plan of an investment project involves environmental professionalsexperts in the field of relations between humans and nature. The financial expenditures on such consulting services are often tangible, and the design of The importance of decision support in investment has attracted the interest of scientists. Let us cite some scientific works that analyze the issues of designing expert systems for investment. These, in particular, are Jankova Z., Jana D. K., Dostal P. [14], Rutkauskas A. V., Stasytytė V. [15], Vraneg S., Stanojevic M., Stevanovic V., Lucin M. [16], Zargham M., Mogharreban N. [17], etc.
Much of the research related to the development of expert systems in investment is in the field of financial investment. And, as you know, making investment decisions in the real sector of the economy is a challenge that requires attention. We believe that researchers should give due attention to the issues of automating the assessment of the environmental effectiveness of investment projects implemented in the real sector of the economy.

Description of the concept of an expert system designed to assess the environmental effectiveness of investment projects
The authors believe that it is wise to introduce automation into the development of the environmental section of the investment project business plan through an appropriate expert system. Processing input data requested by the system with various prompts and explanations, the expert system should form the environmental section of the business plan under the approved methodology for investment project efficiency evaluation. Such an expert system can be in demand by consulting companies that provide businessplanning services. In addition, its users can be individual enterprises (companies) wishing to implement a certain investment project in the real economy and designing a business plan inhouse.
The creation of such an expert system requires various specialists: ecologists, economists, project management specialists, programmers, knowledge engineers, lawyers, etc. The Russian Federation has highly qualified specialists in all of the above areas of knowledge. Therefore, the creation of this system is realistic. Moreover, the architecture of the system should not depend on the specifics of certain regions. It can be the same for all regions of the Russian Federation. The difference will be in filling this system with knowledge, the specific nature of which will depend on the current environmental legislation and natural resources (flora, fauna) in each region, as well as on the features that characterize the region. Therefore, local environmental experts should be involved in filling this system with knowledge.
This expert system should be universal and take into account various loads on the natural environment caused by construction, the launch of a manufacturing line, product release, etc.
Examples of input data into an expert system are a site for construction or production, the volume of load (for example, the scale of construction or turnout), the type of products, etc.
The proposed system should play the role of a consultant in the field of environmental legislation. Moreover, it should offer the user a list of environmental protection measures corresponding to their project, which will help significantly reduce the load on the natural environment.
The main functional characteristics of the expert system proposed for creation are in the Use Case Diagram (see Figure 2). The created expert system should possess the following qualities [6]: user-friendly, flexible, easy to be modified, and able to propose solutions for various problems. We completely agree that "…an expert system should be well designed so as to meet the requirements for a software to store knowledge, explain problems, and recommend solutions" [6].

Concerning certain aspects of creating the expert system
Separately, we would like to examine some aspects of creating the expert system, related to identifying homogeneous and/or close estimates in a group of experts, as well as to the possible use of the hierarchy analysis method in the corresponding intelligent information system.
As noted above, the design of the expert system will require the participation of various specialists, i.e. a group of experts with individual experience, knowledge, abilities, skills, the level of professionalism and competence, preferences, ideas, judgments, and intuition. We emphasize that the group involved in creating the expert system may include several specialists in one field of activity, for instance, several environmental experts. As each specialist adheres to their system of judgments, it becomes necessary to identify the point of view dominated in the group of experts. Identifying the point of view dominated in the group of experts can be reduced to the search for common elements (see, for instance, [18; 19]).
Finally, in many actual situations, the analysis of complex problems and, in particular, managerial decision-making can be based on Thomas Saaty's hierarchy analysis method (see, for instance, [20]). The hierarchy analysis method seems more justified for multi-criterion problems in a complex environment with hierarchical structures than an approach based on linear logic. The hierarchy analysis method implies decomposing the problem into more and more simple components and processing the judgments of the decision-maker. It results in identifying the relative importance of the investigated alternatives for all criteria in the hierarchy. Relative importance is expressed numerically as priority vectors. The vectors' values obtained in such a way are estimates on the ratio scale and correspond to the so-called hard estimates.

Conclusions
The design and application of the expert system proposed by the authors will lead to several positive effects: faster development of project materials, improved quality of planning, reduced number of mistakes, lower cost of assessment, increased confidence in the environmental section of the business plan by third-party participants (including representatives of the government), increased literacy of users of the expert system in the field of environmental protection. Such an intelligent information system can be created for each region of the Russian Federation (the structure of the system will be the same; the only difference will be in its filling with knowledge). This expert system needs constant updates to comply with the current legislation.
Our further research in this direction will be related to the development of the architecture of the proposed expert system.