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A new hybrid genetic algorithm and its application to the temperature neural network prediction in TFIH

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5 Author(s)
Tanggong Chen ; Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Box 359, Tianjin 300130, China ; Youhua Wang ; Lingling Pang ; Jingfeng Sun
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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 algorithm is better than that of GA or PSO.

Published in:

2008 World Automation Congress

Date of Conference:

Sept. 28 2008-Oct. 2 2008