An Improved PSO Algorithm to Optimize BP Neural Network

Abstract

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