Study on Passenger Traffic Volume Forecast of High-speed Railway

被引：0
|
作者：
Mu, Hai-bo [1 ]
Sun, Li [1 ]
机构：
[1] Lanzhou Jiaotong Univ, Sch Traff & Transportat Engn, Lanzhou, Gansu, Peoples R China
来源：
2017 2ND INTERNATIONAL CONFERENCE ON COMPUTATIONAL MODELING, SIMULATION AND APPLIED MATHEMATICS (CMSAM) | 2017年
关键词：
Passenger traffic volume of high-speed railway; Partial least-squares regression; Grey forecasting model; IOWA combination forecast;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
To improve the forecasting accuracy of the future passenger traffic volume of high-speed railway in our country, a combinational forecasting method based on induced ordered weighted averaging (IOWA) operator is proposed, and the optimal combined forecasting model based on IOWA operator is established by regarding the sum of error squares as a criterion. Finally, the passenger traffic volume of high-speed railway during the 13th five-year is predicted by using IOWA combination model. It indicates that the proposed method in this article can effectively improve the prediction accuracy, and it is suitable for predicting our country's passenger traffic volume of high-speed railway.
引用
收藏
页码：355 / 360
页数：6
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