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In this paper, an adaptive population disappearance genetic algorithm called APDGA is presented. APDGA enlightened by the phenomenon of mutation and disaster in the biology evolutionary process can improve the population distribution, restrain premature convergence and enhance the ability of whole convergence. This method is applied to electromagnetic device optimization successfully. Simulation shows...
Based on the analysis of the characters of genetic algorithm (GA) and particle swarm optimization (PSO), a new hybrid genetic algorithm is presented. This method integrates the well-known GA with PSO by embedding particle swarm operator into GA, and is applied to the temperature neural network (NN) prediction in transverse flux induction heating (TFIH). The results show that the performance of this...
A procedure is presented for optimal design of transverse flux inductor. To improve the convergence speed and local searching ability for genetic algorithm, subpopulation competition and data exchange method is proposed. One purpose of that is for basic population to decide when to produce a new subpopulation; the other purpose is to introduce quality individuals from subpopulation into basic population...
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