Application of BP Neural Network Forecast Model Based on Principal Component Analysis in Railways Freight Forecas

Authors:
Zhou Jianguo;Qin Gang
Affiliations:
-;-
Venue:
CSSS '12 Proceedings of the 2012 International Conference on Computer Science and Service System
Year:
2012

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Abstract

This paper uses the BP neural network forecast model based on principal component analysis to predict China's railways freight. It firstly regroups indexes affecting railways freight by principal component analysis as to make the dimensions of index reduced and unrelated, and then it makes use of BP neural network to built model, and predicts the railways freight. The forecast result indicates that the method this paper uses has high prediction accuracy.