基于时间序列方法的全国铁路旅客周转量的分析与预测

Analysis and Forecast for the National Railway Passenger Turnover Volume Based on Time Series Method

应用两种时间序列分析的方法对全国铁路旅客周转量的月度数据进行分析.运用X-11方法和季节ARIMA模型进行分析并分别对未来5个月的周转量做了预测,结果表明季节ARIMA模型优于X-11方法.通过对全国铁路旅客周转量的定量分析,为铁路部门在计算运输成本,劳动生产率,旅客平均行程等方面提供有效的依据.

This paper applied two methods of time series analysis to analyze monthly data of the national railway passenger turnover volume. By using X-11 method a seasonal ARIMA model to predict the turnover for the next 5 months.The results show that seasonal ARIMA model results is better than that of X-11 method. Through the quantitative analysis of national railway passenger turnover, we can provide an effective basis for the calculation of transport costs in terms of labor productivity, average passenger itineraries.