SEARCH FOR OPTIMAL FUNCTIONS OF FUZZY SYSTEMS BASED ON BIOINSPIRED EVOLUTIONARY ALGORITHMS

Abstract

Contemporary research in the field of creation and development of intelligent systems based on fuzzy logic is carried out mainly in the direction of developing highly efficient methods for their synthesis and structural-parametric optimization. In recent years, due to the intensive development of information technologies and computer hardware, bioinspired intelligent techniques of global search are quite promising for solving problems of synthesis and optimization of fuzzy systems, which include evolutionary and swarm methods, that simulate the processes of natural selection, as well as collective behavior of various groups of social animals, insects and microorganisms in nature. This paper is devoted to the development and study of a method of optimal membership functions search for fuzzy systems based on bioinspired evolutionary algorithms of global optimization. The obtained method allows finding the optimal membership functions of linguistic terms at solving the compromise problems of multicriteria structural optimization of various fuzzy systems in order to increase their efficiency, as well as to reduce the degree of complexity of further parametric optimization. In the proposed method for finding the global optimum of the problem being solved, the iterative procedures are carried out on the basis of combination of several different bioinspired evolutionary algorithms with subsequent analysis of the results obtained and the choice of the best variant of the membership function vector. The paper outlines the theoretical foundations and information model for the implementation of the computational step-by-step method for structural optimization of fuzzy systems, as well as presents various options for carrying out its search procedures. In particular, the features of the application and adaptation to the search problem to be solved of such bioinspired evolutionary algorithms as genetic, artificial immune systems and biogeographic are discussed.