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Soft Computing
Published in: Soft Computing 3/2016

23-12-2014 | Methodologies and Application

Dynamic parameter adaptation in particle swarm optimization using interval type-2 fuzzy logic

Authors: Frumen Olivas, Fevrier Valdez, Oscar Castillo, Patricia Melin

Published in: Soft Computing | Issue 3/2016

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Abstract

In this paper, we propose a new method for dynamic parameter adaptation in particle swarm optimization (PSO). PSO is an optimization method inspired in social behavior, which has been applied to different optimization problems obtaining good results. In this paper, we propose an improvement to the convergence and diversity of the swarm in PSO using interval type-2 fuzzy logic. Simulation results show that the proposed approach improves the performance of PSO. A comparison of the proposed method using type-2 fuzzy logic with the original PSO approach, and with PSO using type-1 fuzzy logic for dynamic parameter adaptation is presented.
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Metadata
Title
Dynamic parameter adaptation in particle swarm optimization using interval type-2 fuzzy logic
Authors
Frumen Olivas
Fevrier Valdez
Oscar Castillo
Patricia Melin
Publication date
23-12-2014
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 3/2016
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-014-1567-3

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