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作者:

Zhou, Hanxiao (Zhou, Hanxiao.) | Zhou, Leishan (Zhou, Leishan.) | Guo, Bin (Guo, Bin.) | Bai, Zixi (Bai, Zixi.) | Wang, Zeyu (Wang, Zeyu.)

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EI Scopus SCIE

摘要:

With the continuous expansion of the railway infrastructure network, the railway operation network has become more and more complex both in time and space dimensions. In order to help railway operators formulate management measures more pertinently, this research aims to develop a method to analyze the complex operation network via quantifying and ranking the importance of stations in different periods based on the train timetable. Firstly, we propose the time-space train origin-destination (OD) service network (OD-TS network) to abstractly describe the railway transportation service. And a network construction method is designed to build the OD-TS network according to the train operation information in the timetable. We further develop an improved k-shell decomposition method to quantify the node importance for the directed-weighted networks. Case studies are carried out based on the train timetable of China's high-speed railway. We study the OD-TS network from three perspectives (the global network, the railway hubs, and the stations) and analyze the spatiotemporal details of the railway operation. These analyses show that the proposed method can help the railway operators mine the spatiotemporal characteristics of the railway operation well.

关键词:

Spatiotemporal phenomena Economics planning transportation systems analysis Data analysis scheduling complex networks Indexes System analysis and design Big Data service network design Rail transportation Scheduling Complex networks Big data analytics of networks Public transportation

作者机构:

  • [ 1 ] [Zhou, Hanxiao]China Acad Railway Sci Corp Ltd, Sci & Tech Informat Res Inst, Beijing 100081, Peoples R China
  • [ 2 ] [Zhou, Hanxiao]Zhejiang Rail Transit Operat Management Grp CO LT, Haining 310020, Zhejiang, Peoples R China
  • [ 3 ] [Zhou, Leishan]Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing 100044, Peoples R China
  • [ 4 ] [Guo, Bin]Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing 100044, Peoples R China
  • [ 5 ] [Guo, Bin]Beijing Jiaotong Univ, Frontiers Sci Ctr Smart High Speed Railway Syst, Beijing 100044, Peoples R China
  • [ 6 ] [Bai, Zixi]Beijing Univ Technol, Fac Architecture Civil & Transportat Engn, Beijing Key Lab Traff Engn, Beijing 100124, Peoples R China
  • [ 7 ] [Wang, Zeyu]Beijing Infrastruct Investment Co LTD, Beijing 100101, Peoples R China

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来源 :

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING

ISSN: 2327-4697

年份: 2022

期: 6

卷: 9

页码: 4209-4219

6 . 6

JCR@2022

6 . 6 0 0

JCR@2022

JCR分区:1

中科院分区:2

被引次数:

WoS核心集被引频次: 4

SCOPUS被引频次: 5

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 6

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