Constructing a user-friendly GA-based fuzzy system directly from numerical data

Author

Teng, You-Wei ; Wang, Wen-June

Author_Institution

Dept. of Electr. Eng., Nat. Central Univ., Chung-li, Taiwan

Volume

34

Issue

5

fYear

2004

Firstpage

2060

Lastpage

2070

Abstract

This paper proposes a novel genetic algorithms (GA)-based algorithm to construct a user-friendly fuzzy system for approximating an unknown system with a satisfactory degree of accuracy. In the algorithm, the adequate number of fuzzy rules, the adequate number of membership functions of each input variable, and the parameters of membership functions will be determined automatically; in addition, the dummy input variables will be detected and discarded. Finally, several typical examples are illustrated to show the effectiveness of the algorithm.

Keywords

fuzzy set theory; fuzzy systems; genetic algorithms; learning (artificial intelligence); least squares approximations; nonlinear systems; parameter estimation; fuzzy rules; fuzzy sets; genetic algorithms; least-squares methods; membership functions; numerical data; parameter estimation; user-friendly GA-based fuzzy system; Fuzzy sets; Fuzzy systems; Genetic algorithms; Input variables; Iterative algorithms; Parameter estimation; Power generation; Algorithms; Fuzzy Logic; Least-Squares Analysis; Models, Statistical; Nonlinear Dynamics; Numerical Analysis, Computer-Assisted;

fLanguage

English

Journal_Title

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on

Publisher

ieee

ISSN

1083-4419

Type

jour

DOI

10.1109/TSMCB.2004.833600

Filename

1335500