Local and global estimation of Takagi-Sugeno consequent parameters in genetic fuzzy systems

Author

Delgado, Myriam Regattieri ; Von Zuben, Fernando ; Gomide, Fernando

Author_Institution

Dept. of Comp. Eng. & Ind. Autom., Univ. Estadual de Campinas, Sao Paulo, Brazil

Volume

3

fYear

2001

fDate

25-28 July 2001

Firstpage

1247

Abstract

In modular and hierarchical evolutionary design of Takagi-Sugeno (T-S) fuzzy systems, an important issue involves the determination of an effective procedure to optimize rule consequent parameters. All the aspects associated with the antecedent part of each fuzzy rule are evolved through generations, and given a specification of the antecedent part of the rules that compose a candidate fuzzy system, the best set of consequent parameters should be determined. This paper investigates the use of global and local least squares optimization procedures to perform this task. Function approximation problems are solved to test the performance of the evolutionary process in comparison with alternative solutions

Keywords

fuzzy logic; genetic algorithms; least squares approximations; parameter estimation; uncertainty handling; T-S fuzzy systems; Takagi-Sugeno consequent parameters; antecedent part; approximate reasoning methods; candidate fuzzy system; function approximation problems; fuzzy rule; fuzzy rule-based systems; genetic algorithms; genetic fuzzy systems; global least squares optimization; hierarchical evolutionary design; local least squares optimization; rule consequent parameter optimisation; Biological cells; Computer industry; Design engineering; Design optimization; Fuzzy sets; Fuzzy systems; Genetic engineering; Least squares methods; Takagi-Sugeno model; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th

Conference_Location

Vancouver, BC

Print_ISBN

0-7803-7078-3

Type

conf

DOI

10.1109/NAFIPS.2001.943726

Filename

943726