ISSN 1991-2927
 

ACP № 3 (61) 2020

Author: "Maksim Mikhailovich Gorokhov"

Grigorii Aleksandrovich Blagodatskii, Kalashnikov Izhevsk State Technical University, Candidate of Engineering; Associate Professor at the Department of Information Systems of Kalashnikov Izhevsk State Technical University; an author of articles and monographs in the field of automation and optimization of business processes of enterprises and certificates of registration of databases and computer programs. [e-mail: blagodatsky@gmail.com]G. Blagodatskii,

Maksim Mikhailovich Gorokhov, Kalashnikov Izhevsk State Technical University, Doctor of Physics and Mathematics; Professor; Head of the Department of Information Systems of Kalashnikov Izhevsk State Technical University; an author of articles and monographs in the field of development and design of software and hardware tools for various purposes as well as the certificates of registration of databases and computer programs. [e-mail: insys2005@mail.ru]M. Gorokhov,

Denis Alekseevich Perevedentcev, Kalashnikov Izhevsk State Technical University, Postgraduate Student at the Department of Information Systems of Kalashnikov Izhevsk State Technical University; an author of articles and monographs in the field of design and development of expert systems for supporting the processes of management of research and innovation projects as well as the certificate of registration of databases and computer programs. [e-mail: perevedencew@mail.ru]D. Perevedentcev

Modelling the System of Fuzzy Logical Inference for Evaluating Science-intensive Projects 000_11.pdf

In order to determine the innovative potential and prospects of science-intensive projects, it is required to account for a large number of parameters that covers the whole interaction system of the specific time with the environment. The purpose of the study is developing models, methods, algorithms and software for processes aimed at improving the efficiency of management of research and innovation projects. Today, fuzzy inference is widely used in modeling systems characterized by predominantly qualitative parameters. In order to solve the problem, a fuzzy logic system based on the Mamdani algorithm was developed. With the use of factor analysis, eight factors from the total set of projects’ parameters were identified. In the estimates of the factors of the project state, several ranges of values were revealed and the respective linguistic variables were implemented. The result of the application of author’s algorithms is a system of fuzzy inference built in the Matlab FUZZY environment. The system describes the commercial appeal, level of completion and prospects of knowledge-intensive projects. On the basis of the calculated characteristics of the project, the algorithm of evaluation of science projects was developed. The algorithm of solving the problem of multi-objective optimization for selecting projects from the database was presented.

Fuzzy inference, high-tech projects, complex systems, effective evaluation, algorithm of evaluation, selection algorithm.

2017_ 2

Sections: Artificial intelligence

Subjects: Artificial intelligence, Information systems.


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