Evolutionary computing for fuzzy system optimization in intelligent control

被引：0
|
作者：
Castillo, O [1 ]
Huesca, G [1 ]
Valdez, F [1 ]
机构：
[1] Tijuana Inst Technol, Dept Comp Sci, Tijuana, Mexico
来源：
IC-AI '04 & MLMTA'04 , VOL 1 AND 2, PROCEEDINGS | 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 system.
引用
收藏
页码：98 / 104
页数：7
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