A fuzzy modeling of very large scale system using genetic algorithm and a multiple-representing method

Author

Yoshikawa, Tomohiro ; Furuhashi, Takeshi ; Uchikawa, Yoshiki

Author_Institution

Dept. of Inf. Electron., Nagoya Univ., Japan

fYear

1994

fDate

26-29 Jun 1994

Firstpage

1895

Abstract

The paper presents a new approach to fuzzy modeling of very large scale systems using a genetic algorithm. A new method for obtaining multiple phenotypes from a chromosome, i.e. a multiple-representing method, for expanding exploratory space is also proposed. The new method maintains the diversity of the phenotypes and is effective in exploring the vast solution space. A simulation of fuzzy modeling to identify a multi-input nonlinear system is done to show the effectiveness of the proposed method

Keywords

fuzzy logic; fuzzy set theory; genetic algorithms; knowledge based systems; large-scale systems; modelling; exploratory space; fuzzy modeling; genetic algorithm; multi-input nonlinear system; multiple phenotypes; multiple-representing method; solution space; very large scale system; Biological cells; Computational modeling; Diversity methods; Fuzzy systems; Genetic algorithms; Large-scale systems; Nonlinear equations; Nonlinear systems; Packaging; Space exploration;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1896-X

Type

conf

DOI

10.1109/FUZZY.1994.343570

Filename

343570