铁路货运短期需求预测

Prediction of Rail Freight Short-term Demand

精确的铁路货运量预测是制定铁路货物运输计划的基础。首先对三项短期预测模型ARMA预测、多元回归预测、灰色预测方法进行了研究,接着对这三种预测方法采取最优加权的方式进行组合,最后得出研究结果:组合预测相比单个预测模型精确度高,对铁路货运需求预测有更好的指导意义。

The accurate demand prediction is the foundation of railway goods transportation planning. This paper studies the theory of ARMA prediction,multi linear regression and grey system,and uses the method of optimal weighted combination to forecast the short- term needs. Finally,the results show that： compared with single model,the accuracy of combination model is high,and has very good guidance significance to the railway freight demand forecasting.