大型客运站人流量在线预测模型研究  

Research on online prediction model of passenger flow in railway station

作　　者：詹玉广 Zhan Yuguang(China Railway Investment Co.,Ltd.,Beijing 100055,China)

机构地区：[1]中国铁路投资有限公司,北京100055

出　　处：《国外电子测量技术》2020年第11期94-97,共4页Foreign Electronic Measurement Technology

摘　　要：车站作为铁路交通的枢纽和人员调度的载体,是影响铁路运输的关键因素。车站人员的流动影响着车站的运营和负载冗余情况,而合理有效的客流量预测可以为车站安防、资源调配以及人员部署提供依据和保障。采用神经网络对车站客流量进行预测,分析并选择影响车站客流量变化的关键因素作为神经网络的输入,通过在线学习和变步长速率更新的方法对车站不同时段的进站人数进行估计,同时对历史数据和估计数据进行加权平均得到下一时段客流量的预测值。仿真结果说明该预测模型具有良好的效果。As the hub of railway transportation and the carrier of staff scheduling,railway station is the key factor which affects the railway passenger transport.Passenger flow has a directly effect on station operation and load redundancy,while an effective prediction of passenger flow can guarantee the station security,staff assignment and resource allocation.The neural network is taken to predict the passenger flow,and the factors which affect the variety of passenger flow are analysis and selected as the input of neural network.The online learning and variable step rate update are adopted to estimate the number of the passenger during a certain period,which is then weighted with the historical data to derive the prediction of passenger of the next period.The simulation demonstrates that the prediction model can obtain a well result.

关 键 词：火车站 客流量 神经网络 在线预测 

分 类 号：U293.13[交通运输工程—交通运输规划与管理]