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.
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Olivas, F., Valdez, F., Castillo, O. (2015). Fuzzy Classification System Design Using PSO with Dynamic Parameter Adaptation Through Fuzzy Logic. In: Castillo, O., Melin, P. (eds) Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics. Studies in Computational Intelligence, vol 574. Springer, Cham. https://doi.org/10.1007/978-3-319-10960-2_2
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DOI: https://doi.org/10.1007/978-3-319-10960-2_2
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