Prediction model of Passenger Waiting Time in High-speed Rail Hub Based on BP Neural Network

被引：3
|
作者：
Yu-Long Pei [1 ]
Kan Zhou [1 ]
Ting Peng [1 ]
机构：
[1] Harbin Inst Technol, Sch Traff Sci & Engn, Harbin 150090, Peoples R China
来源：
MECHATRONICS AND INDUSTRIAL INFORMATICS, PTS 1-4 | 2013年 / 321-324卷
关键词：
Traffic engineering; Waiting time; BP neural network; Prediction; High-speed rail hub; SERVICE;
D O I：
10.4028/www.scientific.net/AMM.321-324.1903
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In order to explore the characteristics of passenger waiting time in high-speed rail hub, this paper analyzed the influencing factors of passenger waiting time, based on the survey of passenger waiting time in high-speed rail hub. And the main influencing factors were screened out using variance analysis. Then the prediction model of passenger waiting time based on BP neural network was established, the parameters of the model were calibrated and the validity was verified. The results show that, travel time in urban area, trip distance, familiarity toward the hub, educational background of passengers, and the type of transportation is the main influencing factor of passenger waiting time in high-speed rail hub, and the average relative error is only 9.2% using the proposed prediction model of passenger waiting time based on BP neural network.
引用
收藏
页码：1903 / 1906
页数：4
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