An Improved PSO Algorithm to Optimize BP Neural Network

This paper presents a new BP neural network algorithm which is based on an improved particle swarm optimization (PSO) algorithm. The improved PSO (which is called IPSO) algorithm adopts adaptive inertia weight and acceleration coefficients to significantly improve the performance of the original PSO algorithm in global search and fine-tuning of the solutions. This study uses the IPSO algorithm to optimize authority value and threshold value of BP nerve network and IPSO-BP neural network algorithm model has been established. The results demonstrate that this model has significant advantages inspect of fast convergence speed, good generalization ability and not easy to yield minimal local results.