基于ARMA模型与多元回归的甘宁区铁路货运量预测

Freight Volume Forecast of Gan-Ning District Railway Based on ARMA Model and Multiple Regression

合理的预测铁路货运量是铁路运输部门制定列车开行方案的基础,并且了解其变化情况对开展铁路运输工作有重要的参考依据。本文选取甘宁区2008—2019年时间序列数据,采用ARMA模型与多元线性回归模型相结合的方法,对甘宁区铁路年度货运量进行分析及预测。选取铁路货运量的多个影响因素,利用多元线性回归模型对甘宁区铁路货运量的影响因素进行实证分析,找出对铁路货运量影响显著的因素;在此基础上,用EViews10.0拟合ARMA模型,最终得出甘宁区铁路货运量未来五年的预测值,并分析其变化趋势,结合甘宁区铁路货运量的现状,提出改进建议。

Reasonable prediction of railway freight volume is the basis for railway transportation departments to formulate train operation plans, and understanding the changes is an important reference for carrying out transportation work. This paper selects the time series data of Gan-Ning District from 2008 to 2019, and uses the method of combining the ARMA model and the multiple linear regression model to predict the annual freight volume of railways in Gan-Ning District. We select multiple influencing factors of railway freight volume, use multiple linear regression model to conduct empirical analysis on the influencing factors of railway freight volume in Gan-Ning District, and find out the factors that have significant impact on railway freight volume. On this basis, EViews10.0 is used to simulate Integrating the ARMA model, the predicted value of the railway freight volume in Gan-Ning District in the next five years is finally obtained, and its change trend is analyzed. Combined with the current situation of the railway freight volume in Gan-Ning District, and suggestions for improvement are put forward.