基于GM—周期扩展组合模型的铁路客运量预测

Railway passenger volume forecast periodic based on GM-periodic extended portfolio model

铁路客运量的准确预测对我国铁路建设项目投资和决策具有重要意义。由于铁路客运量预测系统本身是一个信息不完全的灰色系统,因此,可以通过建立(灰色)GM-周期扩展组合模型对铁路客运量的非线性动态变化进行预测。该模型运用灰色预测理论GM(1,1)与周期扩展模型结合,不但可以进行客运量的趋势预测,同时也可以充分考虑铁路客运量的周期波动性这一特征。最后,结合具体的实例验证说明该模型是科学合理的,预测值与实际值较吻合。

Accurate prediction of passenger rail system has important significance for China＇s railway construction investment and decision -making.Since the railway passenger traffic forecasting system itself is a gray incom-plete information system,the establishment of （gray）GM-expanded combined -cycle model of nonlinear dy-namically changed in railway passenger traffic volume forecast.The use of gray prediction model GM （1,1 ） model with cycle expansion,can not only predict trends in passenger traffic,but can also fully take into account the cyclical fluctuations of the railway passenger traffic volume of this feature.Finally,with specific examples validation that the model is scientific and rational,predicted value and the actual value is more consistent.