Railway Freight Volume Forecast Based on GRA-WD-WNN

After analyzing the influencing factors of railway freight volume, the WD-WNN forecast method of railway freight volume based on grey correlation analysis is proposed, in order to improve the prediction accuracy of regional railway freight volume. The gray correlation analysis method is used to analyze the correlation between the freight volume and its influencing factors, and WNN input variables are selected by the gray correlation. Then the influencing factors original sequence are denoised by WD technology to improve the smoothness of the input variables. Finally, the freight volumes are trained and predicted by the WNN prediction model. The analysis of the freight volume of Qinghai Province in China from 1990 to 2017 shows that the GRA-WD-WNN method has a faster convergence speed and higher prediction accuracy, and the average relative error of the prediction results is only 4.30%.