Classifications of Stations in Urban Rail Transit based on the Two-step Cluster

被引：15
|
作者：
Li, Wei [1 ,2 ,3 ]
Zhou, Min [1 ]
Dong, Hairong [1 ]
机构：
[1] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
[2] Beijing Transportat Informat Ctr, Beijing 100073, Peoples R China
[3] Beijing Key Lab Comprehens Transportat Operat & S, Beijing 100073, Peoples R China
来源：
INTELLIGENT AUTOMATION AND SOFT COMPUTING | 2020年 / 26卷 / 03期
关键词：
Two-step cluster; urban rail transit; station classification; time series; principal component analysis; spatial-temporal data analysis;
D O I：
10.32604/iasc.2020.013930
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Different types of stations have different functional roles in the urban rail transit network. Firstly, based on the characteristics of the urban rail transit network structure, the time series features and passenger flow features of the station smart card data are extracted. Secondly, we use the principal component analysis method to select the suitable clustering variables. Finally, we propose a station classification model based on the two-step cluster method. The effectiveness of the proposed method is verified in the Beijing subway. The results show that the proposed model can successfully identify the types of urban rail transit stations, clarify the function and orientation of each station.
引用
收藏
页码：531 / 538
页数：8
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