交通运输工程与信息学报2019，Vol.17Issue(1)：25-32,8.DOI:10.3969/j.issn.1672-4747.2019.01.005
基于SARIMA模型的铁路月度客运量预测
Monthly Railway Passenger Traffic Volume Forecasting Based on SARIMA Model
汤银英 1朱星龙 2李龙1
作者信息
- 1. 西南交通大学, 交通运输与物流学院, 成都 610031
- 2. 综合交通运输智能化国家地方联合工程实验室, 成都 610031
- 折叠
摘要
Abstract
The data sequence of monthly railway passenger traffic volume exhibits a trend of linear growth in the long term, but it fluctuates significantly with the month in the short term. This study uses the SARIMA model to accurately predict monthly railway passenger traffic volume for 2016 and determine the seasonal fluctuations in monthly traffic, which can provide an important reference for the railway department in adjusting train diagrams and planning passenger trains. It can also help railway terminal staff know passenger peak times in advance, and can improve the efficiency of railway passenger transport organizations.关键词
铁路/客运量/SARIMA模型/预测Key words
railway/passenger traffic volume/SARIMA model/forecasting分类
交通工程引用本文复制引用
汤银英,朱星龙,李龙..基于SARIMA模型的铁路月度客运量预测[J].交通运输工程与信息学报,2019,17(1):25-32,8.
