Grey Wolf Optimizer with dynamic adaptation of parameters using fuzzy logic

被引：0

作者：

Rodriguez, Luis ^{[1
]}

Castillo, Oscar ^{[1
]}

Soria, Jose ^{[1
]}

机构：

[1] Tijuana Inst Technol, Tijuana, Mexico

来源：

2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2016年

关键词：

dynamic adaptation; fuzzy logic; performance; GWO; benchmark functions;

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：

The main goal of the paper is the use of fuzzy logic for dynamic parameter adaptation in the Grey Wolf Optimizer (GWO) algorithm. The proposed approach of a fuzzy GWO is compared with the traditional GWO algorithm with a set of benchmark functions. Simulation results show that there is a significant advantage of the proposed fuzzy GWO.

引用

页码：3116 / 3123

页数：8

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