Paper Info
Title
Evolutionary design of Takagi-Sugeno fuzzy systems: a modular and hierarchical approach
Abstract
This paper improves some results associated with a modular and hierarchical evolutionary design of fuzzy systems, using a Takagi-Sugeno approach. Basically, the set of design parameters to be adjusted is divided into modules distributed over different levels that evolve in an interactive way. Due to the existence of a compromise between the flexibility of the fuzzy system architecture and the efficiency of the evolutionary process, a significant gain in performance can be obtained when the set of parameters to be automatically defined is divided into two groups: one optimized using a least square procedure, and the other evolved using genetic algorithms. simulation results show that the proposed method increases computational tractability and favor the descriptive nature of the final solution.
Year
DOI
Venue
2000
10.1109/FUZZY.2000.838701
NINTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2000), VOLS 1 AND 2
Keywords
DocType
Citations 
genetic algorithm,fuzzy systems,fuzzy sets,design automation,least square,genetic algorithms,fuzzy system
Conference
8
PageRank 
References 
Authors
0.72
6
4
Name
Order
Citations
PageRank
Myriam Regattieri Delgado122422.26
Fernando Von Zuben2614.04
Fernando Gomide363149.76
MR Delgado480.72