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《Journal of Chongqing University of Technology(Natural Science)》 2015-11
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An Adaptive Chaotic Particle Swarm RBF Neural Network Optimization Algorithm

ZHANG Yi;TIAN Ai-kui;HAN Shi-yuan;College of Computer Science and Technology,Shandong University of Technology;School of Information Science and Engineering,University of Jinan;  
In order to improve the prediction results of RBF neural network,this paper proposed an adaptive chaos particle swarm optimization algorithm of RBF neural network( SACPSO-RBF) according to the shortcomings of the RBF neural network. This algorithm mainly used the adaptive chaotic particle swarm optimization algorithm to optimize the RBF neural network. The use of variation between individuals,the cross over operation and individual chaos disturbance can effectively avoid the local convergence of the particle swarm optimization algorithm. Using the optimization algorithm,we predicted the testing function sequence and tested the validity of the algorithm. Finally,the experimental results show that the algorithm has well prediction ability.
【Fund】: 山东省优秀中青年科学家科研奖励基金资助项目(BS2014DX015)
【CateGory Index】: TP183
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