Title :
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
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;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2004.833600
