采用2006—2010年我国铁路旅客发送量月度数据,建立模型进行时间序列分析,选用求和自回归移动平均模型(ARIMA)拟合原始观察值序列,并使用PASW Statistics 18统计软件辅助完成建模。通过对2010年3—12月铁路旅客发送量进行预测,说明ARIMA模型有比较好的预测效果,可以为提升铁路营运水平提供预测理论和依据。 Using the monthly data of passenger volume of Chinese railways from 2006 to 2010, the model was established for time series analysis. The ARIMA was used to fit the original observations and the PASW Statistics 18 statistical software was used to complete the modeling. By forecasting the amount of railway passengers sent from March to December in 2010, it shows that ARIMA model has better forecasting effect and can provide the theory and basis for improving the railway operation level.