A Review on the Role of Fuzzy Logic in Hybrid Intelligent Systems

Oscar Castillo, Patricia Melin, Fevrier Valdez, Claudia Gonzalez, Mario Garcia, Alejandra Mancilla, Prometeo Cortes-Antonio, Jose Soria

Abstract


In this review the role of fuzzy logic (FL) in hybrid intelligent systems is discussed. We first review the papers in which fuzzy logic is used in conjunction with neural networks, as well as their application areas. Then, we review the papers in which fuzzy logic has been used in combination with evolutionary algorithms, and the corresponding application areas. We also review the papers in which fuzzy logic has been used in a hybrid way with optimization algorithms, as well as the application areas. Regarding FL, we consider the evolution that has been undergoing, where initially type-1 fuzzy logic was proposed and used, later type-2 was proposed and now more recently type-3 has been put forward. The evolution of FL has occurred due to the need of handling the higher uncertainty levels that real world problems have. In this regard, we analyze the impact of this evolution on different types of hybrid intelligent systems.

Keywords


Type-3 fuzzy logic, neural networks, evolutionary algorithms, optimization algorithms

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