Title: Hybrid neural network algorithm method based on particle swarm optimization and BP neural network algorithm
Abstract: For the standard BP(error Back Propagation) algorithm usually has the limitations of slow convergence and local extreme values,a new hybrid BP neural network learning algorithm based on particle swarm optimization(PSO) and BP algorithm was proposed in this paper.The main idea of the model is to find the optima weight for the network by using PSO method and BP algorithm simultaneously.Therefore,it can not only have the global property of PSO but also contain the feature of error back propagation of BP algorithm.The authors evaluate the model by simulation test on some typical complex functions and compare it with other models including standard BP network and traditional PSO based BP network.Experimental results show that the proposed hybrid learning algorithm has higher convergence accuracy,and faster convergence speed.
Publication Year: 2012
Publication Date: 2012-01-01
Language: en
Type: article
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Cited By Count: 1
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