Journal ArticleDOI
Optimal design of fuzzy classification systems using PSO with dynamic parameter adaptation through fuzzy logic
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Simulation results show that the proposed approach to the convergence and diversity of the swarm in PSO using fuzzy logic improves the performance of PSO.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.read more
Citations
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Journal ArticleDOI
Teaching-learning based optimization algorithm based fuzzy-PID controller for automatic generation control of multi-area power system
TL;DR: It is observed that TLBO optimized fuzzy-PID controller gives better dynamic performance in terms of settling time, overshoot and undershoot in frequency and tie-line power deviation as compared to LCOA, GA, PS and SA based PID controllers.
Journal ArticleDOI
A Fuzzy Hierarchical Operator in the Grey Wolf Optimizer Algorithm
Luis Rodríguez,Oscar Castillo,José Soria,Patricia Melin,Fevrier Valdez,Claudia I. Gonzalez,Gabriela E. Martinez,Jesus Soto +7 more
TL;DR: The performance of the Hierarchical GWO algorithm is better when using a fuzzy variant of the hierarchical operator, which is inspired in the hierarchical social pyramid of the grey wolf.
Journal ArticleDOI
Gene selection from microarray gene expression data for classification of cancer subgroups employing PSO and adaptive K-nearest neighborhood technique
TL;DR: Particle swarm optimization method along with adaptive K-nearest neighborhood (KNN) based gene selection technique are proposed to distinguish a small subset of useful genes that are sufficient for the desired classification purpose.
Journal ArticleDOI
Ant colony optimization with dynamic parameter adaptation based on interval type-2 fuzzy logic systems
Frumen Olivas,Fevrier Valdez,Oscar Castillo,Claudia I. Gonzalez,Gabriela E. Martinez,Patricia Melin +5 more
TL;DR: A dynamic parameter adaptation methodology for Ant Colony Optimization (ACO) based on interval type-2 fuzzy systems is presented, to be able to apply this new ACO method with parameter adaptation to a wide variety of problems without the need of finding the best parameters for each particular problem.
Journal ArticleDOI
Optimization of type-2 fuzzy weights in backpropagation learning for neural networks using GAs and PSO
TL;DR: In this paper the optimization of type-2 fuzzy inference systems using genetic algorithms and particle swarm optimization is presented and simulation results and a comparative study are presented to illustrate the advantages of the bio-inspired methods.
References
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