北京交通大学学报2017，Vol.41Issue(6)：42-48,7.DOI:10.11860/j.issn.1673-0291.2017.06.007
基于时空特征的城市轨道交通客流量预测方法
A passenger volume prediction method based on temporal and spatial characteristics for urban rail transit
摘要
Abstract
With the expanding of urban rail transit network revenue length and the increasing of its passenger volume,the passenger volume for some subway stations is susceptible to rapid chan-ges,which can easily incur uneven distribution of the entire network traffic.It could therefore in-crease the difficulty of rail transit operations and probability of operational incidents.On the basis of passenger volume data collected from practical operation,this paper analyzes the temporal and spatial characteristics of the passenger volume.It also proposes a passenger volume prediction method using the Bayesian network to predict the passenger volume of certain subway stations. Based on practical data,these numerical experiments demonstrate that the proposed method can achieve an mean absolute percentage error below 0.1 when predicting,proving the model is highly accurate.关键词
城市轨道交通/客流预测/贝叶斯网络/时空特征Key words
urban rail transit/passenger volume prediction/Bayesian network/temporal and spatial characteristics分类
交通工程引用本文复制引用
袁坚,王鹏,王钺,杨欣..基于时空特征的城市轨道交通客流量预测方法[J].北京交通大学学报,2017,41(6):42-48,7.基金项目
国家自然科学基金(71701013,61673237,71621001 ,71525002) Foundation items:National Natural Science Foundation of China(71701013,61673237,71621001 ,71525002) （71701013,61673237,71621001 ,71525002）
