The Research of Railway Passenger Flow Prediction Model Based on BP Neural Network

被引：7
|
作者：
Wang, Yao [1 ]
Zheng, Dan [2 ]
Luo, Shimin [1 ]
Zhan, Dongming [2 ]
Nie, Peng [1 ]
机构：
[1] East China Jiaotong Univ, Sch Railway Tracks & Transportat, Nanchang 330013, Jiangxi, Peoples R China
[2] East China Jiaotong Univ, Sch Software, Jian 330013, Jiangxi, Peoples R China
来源：
ADVANCED DESIGNS AND RESEARCHES FOR MANUFACTURING, PTS 1-3 | 2013年 / 605-607卷
关键词：
Railway Passenger Flow; Passenger Flow Forecasting; BP Neural Network;
D O I：
10.4028/www.scientific.net/AMR.605-607.2366
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Based on analyzing the principle of BP neural network and time sequence characteristics of railway passenger flow, the forecast model of railway short-term passenger flow based on BP neural network was established. This paper mainly researches on fluctuation characteristics and short-time forecast of holiday passenger flow. Through analysis of passenger flow and then be used in passenger flow forecasting in order to guide the transport organization program especially the train plan of extra passenger train. And the result shows the forecast model based on BP neural network has a good effect on railway passenger flow prediction.
引用
收藏
页码：2366 / +
页数：2
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