Title :
System approximation via GA-based fuzzy model
Author :
Teng, You-Wei ; Wang, Wen-June
Author_Institution :
Dept. of Electr. Eng., Nat. Central Univ., Chung-li, Taiwan
Abstract :
This paper constructs a GA-based fuzzy model to approximate an unknown system without pre-set parameters. A real-coded GA and the least-squares method are applied to search for the antecedent and consequent parameters, respectively. Furthermore, a specific performance index is proposed to determine the optimal number of rules for the fuzzy model, and the adequate number of chromosomes and generations for the real-coded GA such that the approximation accuracy is satisfied.
Keywords :
fuzzy systems; genetic algorithms; least squares approximations; GA-based fuzzy model; approximation accuracy; chromosomes; least-squares method; performance index; pre-set parameters; system approximation; unknown system; Approximation algorithms; Biological cells; Bismuth; Electronic mail; Fuzzy sets; Fuzzy systems; Genetic algorithms; Genetic mutations; Performance analysis; Training data;
Conference_Titel :
Circuits and Systems, 2002. APCCAS '02. 2002 Asia-Pacific Conference on
Print_ISBN :
0-7803-7690-0
DOI :
10.1109/APCCAS.2002.1115333
