A New Methodology for Membership Function Design using Ant Colony Optimization

被引：0
|
作者：
Lizarraga Olivas, Evelia [1 ]
Castillo, Oscar [1 ]
Soria, Jose [1 ]
Melin, Patricia [1 ]
机构：
[1] Tijuana Inst Technol, Tijuana, Mexico
来源：
2013 IEEE SYMPOSIUM ON SWARM INTELLIGENCE (SIS) | 2013年
关键词：
fuzzy control systems; Ant Colony Optimization; evolutive computation;
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：
In this paper we describe a new methodology to optimize fuzzy logic controllers using Ant Colony Optimization (ACO); in particular, the fuzzy logic controller for the water tank benchmark problem. The proposed methodology is applied in the optimization of membership function parameters and type of membership functions, using a set of constraints for the construction of the solution matrix of an ACO algorithm.
引用
收藏
页码：40 / 47
页数：8
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