Optimization of type-2 fuzzy systems based on bio-inspired methods: A concise review

被引：134

作者：

Castillo, Oscar ^{[1
]}

Melin, Patricia ^{[1
]}

机构：

[1] Tijuana Inst Technol, Tijuana 22379, Mexico

来源：

INFORMATION SCIENCES | 2012年 / 205卷

关键词：

Type-2 fuzzy logic; Bio-inspired methods; Optimization; Genetic algorithms; ACO; PSO; MODULAR NEURAL-NETWORKS; WHEELED MOBILE ROBOT; LOGIC CONTROLLERS; RESPONSE INTEGRATION; MEMBERSHIP FUNCTIONS; GENETIC ALGORITHMS; INFERENCE SYSTEMS; UNCERTAINTY; DESIGN; SIMULATION;

D O I：

10.1016/j.ins.2012.04.003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A review of the optimization methods used in the design of type-2 fuzzy systems, which are relatively novel models of imprecision, has been considered in this work. The fundamental focus of the work has been based on the basic reasons of the need for optimizing type-2 fuzzy systems for different areas of application. Recently, bio-inspired methods have emerged as powerful optimization algorithms for solving complex problems. In the case of designing type-2 fuzzy systems for particular applications, the use of bio-inspired optimization methods have helped in the complex task of finding the appropriate parameter values and structure of the fuzzy systems. In this review, we consider the application of genetic algorithms, particle swarm optimization and ant colony optimization as three different paradigms that help in the design of optimal type-2 fuzzy systems. We also provide a comparison of the different optimization methods for the case of designing type-2 fuzzy systems. (C) 2012 Elsevier Inc. All rights reserved.

引用

页码：1 / 19

页数：19

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