Hierarchical genetic algorithms for fuzzy system optimization in intelligent control

被引：0

作者：

Castillo, O ^{[1
]}

Lozano, A ^{[1
]}

Melin, P ^{[1
]}

机构：

[1] Tijuana Inst Technol, Dept Comp Sci, Tijuana, Mexico

来源：

NAFIPS 2004: ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, VOLS 1AND 2: FUZZY SETS IN THE HEART OF THE CANADIAN ROCKIES | 2004年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We describe in this paper the use of hierarchical genetic algorithms for fuzzy system optimization in intelligent control. In particular, we consider the problem of optimizing the number of rules and membership functions using an evolutionary approach. The hierarchical genetic algorithm enables the optimization of the fuzzy system design for a particular application. We illustrate the approach with the case of intelligent control in a medical application. Simulation results for this application show that we are able to find an optimal set of rules and membership functions for the fuzzy control system.

引用

页码：292 / 297

页数：6

共 14 条

[1]

CASTILLO O, SOFT COMPUTING CONTR

[2]

CASTILLO O, SOFT COMPUTING FRACT

[3]

Holland JH, 1992, ADAPTATION NATURAL A, DOI DOI 10.7551/MITPRESS/1090.001.0001

[4] SIMULTANEOUS DESIGN OF MEMBERSHIP FUNCTIONS AND RULE SETS FOR FUZZY CONTROLLERS USING GENETIC ALGORITHMS [J].

HOMAIFAR, A ;

MCCORMICK, E .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1995, 3 (02) :129-139

[5] NEURO-FUZZY MODELING AND CONTROL [J].

JANG, JSR ;

SUN, CT .

PROCEEDINGS OF THE IEEE, 1995, 83 (03) :378-406

[6]

Jang JSR., 1997, NEURO FUZZY SOFT COM

[7]

Karr C. L., 1993, IEEE Transactions on Fuzzy Systems, V1, P46, DOI 10.1109/TFUZZ.1993.390283

[8]

LOZANO A, 2003, THESIS TIJUANA I TEC

[9]

Man K., 1999, Genetic Algorithms: Concepts and Designs, V1st ed.

[10]

MELIN P, MODELLING SIMULATION

← 1 2 →