Optimal design of fuzzy classification systems using PSO with dynamic parameter adaptation through fuzzy logic

  • Authors:
  • Patricia Melin;Frumen Olivas;Oscar Castillo;Fevrier Valdez;Jose Soria;Mario Valdez

  • Affiliations:
  • Tijuana Institute of Technology, Tijuana, Mexico;Tijuana Institute of Technology, Tijuana, Mexico;Tijuana Institute of Technology, Tijuana, Mexico;Tijuana Institute of Technology, Tijuana, Mexico;Tijuana Institute of Technology, Tijuana, Mexico;Tijuana Institute of Technology, Tijuana, Mexico

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2013

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Abstract

In this paper a new method for dynamic parameter adaptation in particle swarm optimization (PSO) is proposed. PSO is a metaheuristic inspired in social behaviors, which is very useful in optimization problems. In this paper we propose an improvement to the convergence and diversity of the swarm in PSO using fuzzy logic. Simulation results show that the proposed approach improves the performance of PSO. First, benchmark mathematical functions are used to illustrate the feasibility of the proposed approach. Then a set of classification problems are used to show the potential applicability of the fuzzy parameter adaptation of PSO.