An optimization method for designing type-2 fuzzy inference systems based on the footprint of uncertainty using genetic algorithms

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• 作者：Denisse  ; Hidalgo^a ; Patricia  ; Melin^b ;   ; ^{epmelin@hafsamx.org} ; Oscar  ; Castillo^b
• 关键词：Type-2 fuzzy logic ; Footprint of uncertainty ; Genetic algorithms ; Design of fuzzy systems
• 刊名：Expert Systems with Applications
• 出版年：2012
• 出版时间：March 2012
• 年：2012
• 卷：39
• 期：4
• 页码：4590-4598
• 全文大小：1159 K

文摘

This paper proposes an optimization method for designing type-2 fuzzy inference systems based on the footprint of uncertainty (FOU) of the membership functions, considering three different cases to reduce the complexity problem of searching the parameter space of solutions. For the optimization method, we propose the use of a genetic algorithm (GA) to optimize the type-2 fuzzy inference systems, considering different cases for changing the level of uncertainty of the membership functions to reach the optimal solution at the end.