Forecast of Railway Freight Volumes Based on LS-SVM with Grey Correlation Analysis

On the basis of analyzing the influencing factors of railway freight volumes,the LS-SVM railway freight volume forecast method with grey correlation analysis was proposed to improve the predicting accuracy and modeling speed of railway freight volumes.The influencing factors of railway freight volumes were divided into social demand factors and railway supply factors.Correlations between the two-category factors and railway freight volumes were analyzed respectively by grey correlation analysis.The input variables of LS-SVM were screened by the grey correlation degree value together with qualitative analysis to simplify the LS-SVM structure.Finally,the stochastic inertia weight PSO(SIWPSO) algorithm was used to optimize the parameters of the LS-SVM model.Statistics of the railway freight volumes from 1980 to 2009 indicate that the proposed forecast method provides a better convergence rate and higher predicting accuracy.