基于数据预处理的铁路客运量灰色预测模型

铁路是国家的基础设施,对铁路的客运量进行准确地预测具有重要的理论意义和实际应用价值。首先对传统预测方法进行了分析,指出它们在运量预测中的不足,进而提出应用灰预测进行运量预测的优势。结合滑动平均法对灰预测方法进行了改进,同时考虑初始条件的改变。在预测2006-2010年全社会客运总量的基础上,根据铁路客运在各种运输方式中所占的份额预测2006-2010年的铁路客运总量。

Research on the grey forecast model to the railway passenger volume based on data pretreatment

The forecasting to the train passenger volume is extremely important in theory and practice since the train is the national infrastructure. The traditional methods of prediction have been analyzed, and their shortcomings in the transportation volume forecast have been pointed out. Then it snggests that the grey prediction takes advantages on the transportation forecast. In order to improve it, it unifies the slip averaging to the grey prediction, simultaneously concerning changing of the initial condition. Forecasting the entire social passenger transportation from 2006 to 2010 year, it forecasts the railway passenger transportation volume from 2006 to 2010 year according to the share that the railway passenger volume occupies in each transport mode .