Title :
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
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;
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
DOI :
10.1109/NAFIPS.2001.943726
