基于X-13A-S季节调整方法的铁路客运量预测分析  

Prediction and analysis about railway passenger volume based on X-13A-S seasonal adjustment method

作　　者：缪巧芬 唐国强[1] 罗耀宁 MIAO Qiao-fen;TANG Guo-qiang;LUO Yao-ning(College of Science,Guilin University of Technology,Gulin 541004,China)

机构地区：[1]桂林理工大学理学院,广西桂林541004

出　　处：《桂林理工大学学报》2018年第3期579-584,共6页Journal of Guilin University of Technology

基　　金：国家自然科学基金项目(41101136);国家社会科学基金项目(13CJY075);广西数量经济学重点实验室项目(2014);广西空间信息与测绘重点实验室项目(15-140-07-33)

摘　　要：依据季节调整思想和X-13A-S模型理论,以传统的SARIMA模型对2000年1月—2016年7月观测值进行建模,预测2016年8—12月铁路客运量,同时用X-13A-S模型对数据中可能存在的日历效应进行季节调整,并建模预测。对比SARIMA模型,X-13A-S模型拟合效果更优,更适合我国铁路客运量的预测。之后用X-13A-S技术将所有原始数据重新建模预测,预计2017年春运后,4月份会再次出现小高峰,将比春运客流高,8月份铁路客运量达到最大。随着假期的减少,10月后客运量将下降,2018年年初迅速回升,总体呈上升趋势。According to the seasonal adjustment and the X-13A-S model theory,firstly we model the observation data between January 2000 and July 2016 with traditional SARIMA model,and make a prediction about railway passenger volume in August 2016 to December 2016.Meanwhile,we make some seasonally adjustments for the calendar effect which possibly existed in the observation data by X13A-S model,then model and predict for them.Compared to the SARIMA model,the X-13A-S model has the better fitting results,more suitable for the forecast of Chinese railway passengers.After that,we remodel and forecast by X-13A-S technology with original observations The result of railway passenger volume is expected to have a small peak in April 2017 after Spring Festival.The transportation passengers will flow higher than the Spring Festival,and achieve a maximum of railway passenger traffic in August.With less holidays after October,railway traffic will decline,but will rebound quickly in early 2018.There is a growing trend in 2018 as a whole.

关 键 词：X-13A-S方法 SARIMA模型 铁路客运量 预测 

分 类 号：F532[经济管理—产业经济]