FA-BP Neural Network-Based Forecast for Railway Passenger Volume

Abstract

The research presents a long-term forecast model based on the use of a back-propagation (BP) neural network. Firstly, a brief overview of the forecast models and BP neural network model is demonstrated. Then the improved BP model based on factor analysis (FA-BP) and algorithmfor solving the model are presented. At last, a numerical case study is shown.As the current statistic yearbook only provides the volume data of Jing-Hu corridor, the notion of economical relation intensityis applied to process the original data. The results show that FA-BP neural network is effective in forecast. The proposed model providesa reference in the forefront field of integrated regional transportation planning.