Application of grey model in prediction for railway freight volume

Prediction of the railway freight volume is the important basis of policy-making departments to make strategies. in practice, itpsilas difficult to get all the information that affect freight transport volume, so using grey forecasting model will reach the target with only poor information. in this paper, the GM (1, 1) model, dynamic GM(1, 1) model and modified residual error GM(1, 1) model are used to predict the rail freight volume and test the precision of the models. The experiment result shows that modified residual error GM(1, 1)model has the highest accuracy and is suitable for short-time forecasting of freight volume.