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

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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.

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Edited by:

Xun Wu, Weizhen Chen, Weijun Yang and Jianguo Liang

Pages:

673-677

Citation:

M. T. Li et al., "FA-BP Neural Network-Based Forecast for Railway Passenger Volume", Applied Mechanics and Materials, Vols. 641-642, pp. 673-677, 2014

Online since:

September 2014

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$38.00

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