DocumentCode :
3783799
Title :
A multi-objective evolutionary algorithm for fuzzy modeling
Author :
F. Jimenez;A.F. Gomez-Skarmeta;H. Roubos;R. Babuska
Author_Institution :
Control Eng. Lab., Delft Univ. of Technol., Netherlands
Volume :
2
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
1222
Abstract :
In this paper a multi-objective evolutionary algorithm with a single run is proposed in order to consider several objectives dealing with transparency and compactness in obtaining a fuzzy model besides the standard accuracy objective. In this way the use of Pareto-optimal solutions within the evolutionary algorithm let us obtain attractive fuzzy models with respect to compactness, transparency and also accuracy. The results of the combination of Pareto-based multi-objective evolutionary algorithms and fuzzy modeling are compared with other approaches in the literature.
Keywords :
"Evolutionary computation","Fuzzy sets","Fuzzy neural networks","Neural networks","Pareto optimization","Control engineering","Laboratories","Fuzzy control","Takagi-Sugeno model","Unsupervised learning"
Publisher :
ieee
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Print_ISBN :
0-7803-7078-3
Type :
conf
DOI :
10.1109/NAFIPS.2001.944781
Filename :
944781
Link To Document :
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