Application of PSO and TLBO algorithms with neural network for optimal design of electrical machines. Issue 2 (5th March 2018) - Kheireddine, Bourahla; Zoubida, Belli; Tarik, Hacib; Imed, Achoui
Abstract : Purpose: This study aims to focus on the application of the stochastic algorithms for optimal design of electrical machines. Among them, the authors are interested in particle swarm optimization and teaching–learning-based optimization. Design/methodology/approach: The optimization process is realized by the coupling of the above methods to finite element analysis of the electromagnetic field. Findings: To improve the performance of these algorithms and reduce their computation time, a coupling with the artificial neuron network has been realized. Originality/value: The proposed strategy is applied to solve two optimization problems: Team workshop problem 25 and switched reluctance motor with flux barriers.