A GENETIC ALGORITHM FOR OPTIMIZING TAKAGI-SUGENO FUZZY RULE BASES

Authors
SIARRY P GUELY F
Citation
P. Siarry et F. Guely, A GENETIC ALGORITHM FOR OPTIMIZING TAKAGI-SUGENO FUZZY RULE BASES, Fuzzy sets and systems, 99(1), 1998, pp. 37-47
Citations number
6
Categorie Soggetti
Statistic & Probability",Mathematics,"Computer Science Theory & Methods","Statistic & Probability",Mathematics,"Computer Science Theory & Methods
Journal title
Fuzzy sets and systems → ACNP
ISSN journal
01650114
Volume
99
Issue
1
Year of publication
1998
Pages
37 - 47
Database
ISI
SICI code
0165-0114(1998)99:1<37:AGAFOT>2.0.ZU;2-U
Abstract
We show that a genetic algorithm can tune the parameters of the member ship functions and outputs of a Takagi-Sugeno fuzzy rule base. The met hod is systematically tested for the approximation of one-input analyt ical function. (C) 1998 Published by Elsevier Science B.V. All rights reserved.