Railway Passenger Volume Forecast Based on IPSO-BP Neural Network

This paper improves the basic particle swarm optimization (PSO) algorithm with adaptive interior and acceleration coefficients which is called IPSO, and use the IPSO algorithm to optimize authority value and threshold value of BP nerve network. Thus IPSO-BP neural network algorithm model has been established and applied into the railway passenger volume forecast. The result shows that this model has significant advantages inspect of fast convergence speed, good generalization ability and not easy to yield minimal local results. In generally, this model exhibits good representation and strong prediction ability, and is a helpful tool in the future railway passenger volume prediction.