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《Journal of Chongqing Institute of Technology(Natural Science)》 2008-09
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IAPSOBPNN Combined Training Algorithms for BP Neural Network

HUANG Li,TANG Wan-mei(College of Mathematics and Computer Sciences,Chongqing Normal University,Chongqing 400047,China)  
BP neural network is easily trapped into local minima,and has low generalization ability.In terms of these problems,IAPSOBPNN(Particle Swarm Optimization with Immunity Algorithm Back Propagation Neural Network)combined training algorithm is proposed,namely: a combination of immunity algorithm,particle swarm optimization and back propagation algorithm.The combined training algorithm is applied to the nonlinear function approximation and stock price forecast with complex nonlinear dynamic characteristic,and the simulation results indicate that the algorithm avoids the network from local minima,enhances the generalization ability of the network,provides a new idea for fixing the parameters of BP network.
【Fund】: 重庆市教委科研项目(KJ060818 KJ060804);; 重庆师范大学校级科研项目(06XLB23)
【CateGory Index】: TP183
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