Evolutionary Optimization of Type-2 Fuzzy Systems Based on the Level of Uncertainty

被引：0
|
作者：
Hidalgo, D. [1 ]
Melin, P. [2 ]
Mendoza, O. [1 ]
机构：
[1] UABC Univ, Sch Engn, Tijuana, Mexico
[2] Tijuana Inst Technol, Tijuana, Mexico
来源：
2010 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2010) | 2010年
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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 an evolutionary method for the optimization of type-2 fuzzy systems based on the level of uncertainty. The proposed evolutionary method produces the best fuzzy inference systems (based on the memberships functions) for particular applications. The optimization of membership functions of the type-2 fuzzy systems is based on the level of uncertainty considering three different cases to reduce the complexity problem of searching the solution space.
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页数：6
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