IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v539y2020ics0378437119316590.html
   My bibliography  Save this article

Identifying critical nodes in metro network considering topological potential: A case study in Shenzhen city—China

Author

Listed:
  • Du, Zhouyang
  • Tang, Jinjun
  • Qi, Yong
  • Wang, Yiwei
  • Han, Chunyang
  • Yang, Yifan

Abstract

How to identify critical nodes in metro networks is still an open and vital topic in complex networks, which has been a key issue in analyzing the structural organization of a network, especially in public transportation. Many effective measures have been developed to solve this problem in undirected or unweighted network. However, statistical indicators of static networks cannot reflect the spatial–temporal characteristics of passenger flow in the metro network. Furthermore, a single measure in critical nodes identification has its own shortcomings causing inaccurate estimation results. In this paper, a novel method for node significance on metro network based on Improved Topological Potential model considering Entropy (ITPE) is proposed. ITPE is utilized to aggregate the multi-measure by considering several different centrality measures to conduct the evaluation of node importance. In order to fully reflect the influence of nodes, topological entropy is adopted and applied to identify the weights of different centrality measures. In addition, invulnerability measurement is used to demonstrate the effectiveness of the proposed node identification method. Finally, the metro transit system in Shenzhen City, China was used as a case study to demonstrate the feasibility of the proposed method. It is found that ITPE method could effectively identify nodes or stations which are crucial both on network structure and passenger flow mobility while traditional undirected and unweighted network cannot completely identify. Accordingly, all the nodes estimated from ITPE method are ranked by the significance, and invulnerability is further used to test the rationality of the identification for critical nodes.

Suggested Citation

  • Du, Zhouyang & Tang, Jinjun & Qi, Yong & Wang, Yiwei & Han, Chunyang & Yang, Yifan, 2020. "Identifying critical nodes in metro network considering topological potential: A case study in Shenzhen city—China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    • Handle: RePEc:eee:phsmap:v:539:y:2020:i:c:s0378437119316590
    DOI: 10.1016/j.physa.2019.122926
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119316590
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.122926?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Soh, Harold & Lim, Sonja & Zhang, Tianyou & Fu, Xiuju & Lee, Gary Kee Khoon & Hung, Terence Gih Guang & Di, Pan & Prakasam, Silvester & Wong, Limsoon, 2010. "Weighted complex network analysis of travel routes on the Singapore public transportation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5852-5863.
    2. Lee, Keumsook & Jung, Woo-Sung & Park, Jong Soo & Choi, M.Y., 2008. "Statistical analysis of the Metropolitan Seoul Subway System: Network structure and passenger flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6231-6234.
    3. Zhang, Shen & Liu, Xin & Tang, Jinjun & Cheng, Shaowu & Qi, Yong & Wang, Yinhai, 2018. "Spatio-temporal modeling of destination choice behavior through the Bayesian hierarchical approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 537-551.
    4. Du, Yuxian & Gao, Cai & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2014. "A new method of identifying influential nodes in complex networks based on TOPSIS," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 57-69.
    5. Latora, Vito & Marchiori, Massimo, 2002. "Is the Boston subway a small-world network?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 109-113.
    6. Zong, Fang & Yu, Ping & Tang, Jinjun & Sun, Xiao, 2019. "Understanding parking decisions with structural equation modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 408-417.
    7. Cervero, Robert & Landis, John, 1993. "Assessing the impacts of urban rail transit on local real estate markets using quasi-experimental comparisons," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(1), pages 13-22, January.
    8. Li, Linbo & Ren, Huan & Zhao, Shanshan & Duan, Zhengyu & Zhang, Yahua & Zhang, Anming, 2017. "Two dimensional accessibility analysis of metro stations in Xi’an, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 414-426.
    9. Phang, Sock-Yong, 2007. "Urban rail transit PPPs: Survey and risk assessment of recent strategies," Transport Policy, Elsevier, vol. 14(3), pages 214-231, May.
    10. de Jong, Martin & Mu, Rui & Stead, Dominic & Ma, Yongchi & Xi, Bao, 2010. "Introducing public–private partnerships for metropolitan subways in China: what is the evidence?," Journal of Transport Geography, Elsevier, vol. 18(2), pages 301-313.
    11. Tang, Jinjun & Zhang, Shen & Chen, Xinqiang & Liu, Fang & Zou, Yajie, 2018. "Taxi trips distribution modeling based on Entropy-Maximizing theory: A case study in Harbin city—China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 430-443.
    12. Chen, Duanbing & Lü, Linyuan & Shang, Ming-Sheng & Zhang, Yi-Cheng & Zhou, Tao, 2012. "Identifying influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1777-1787.
    13. Seaton, Katherine A. & Hackett, Lisa M., 2004. "Stations, trains and small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 635-644.
    14. Sun, Lishan & Huang, Yuchen & Chen, Yanyan & Yao, Liya, 2018. "Vulnerability assessment of urban rail transit based on multi-static weighted method in Beijing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 108(C), pages 12-24.
    15. Yan, Ying & Zhang, Shen & Tang, Jinjun & Wang, Xiaofei, 2017. "Understanding characteristics in multivariate traffic flow time series from complex network structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 149-160.
    16. Zhang, Jianhua & Wang, Shuliang & Wang, Xiaoyuan, 2018. "Comparison analysis on vulnerability of metro networks based on complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 72-78.
    17. Tang, Jinjun & Liang, Jian & Zhang, Shen & Huang, Helai & Liu, Fang, 2018. "Inferring driving trajectories based on probabilistic model from large scale taxi GPS data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 566-577.
    18. Tang, Jinjun & Chen, Xinqiang & Hu, Zheng & Zong, Fang & Han, Chunyang & Li, Leixiao, 2019. "Traffic flow prediction based on combination of support vector machine and data denoising schemes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    19. YalçInkaya, Özgür & Mirac Bayhan, G., 2009. "Modelling and optimization of average travel time for a metro line by simulation and response surface methodology," European Journal of Operational Research, Elsevier, vol. 196(1), pages 225-233, July.
    20. Daniel (Jian) Sun & Yuhan Zhao & Qing-Chang Lu, 2015. "Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China," Sustainability, MDPI, vol. 7(6), pages 1-18, May.
    21. Angeloudis, Panagiotis & Fisk, David, 2006. "Large subway systems as complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 553-558.
    22. Russell Smyth & Ingrid Nielsen & Qingguo Zhai & Tiemin Liu & Yin Liu & C.Y. Tang & Zhihong Wang & Zuxiang Wang & Juyong Zhang, 2008. "Environmental Surroundings And Personal Well-Being In Urban China," Monash Economics Working Papers 32/08, Monash University, Department of Economics.
    23. Graham R. Crampton, 2000. "Urban Economic Structure and the Optimal Rail System," Urban Studies, Urban Studies Journal Limited, vol. 37(3), pages 623-632, March.
    24. Raveau, Sebastián & Muñoz, Juan Carlos & de Grange, Louis, 2011. "A topological route choice model for metro," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 138-147, February.
    25. Barberillo, Josep & Saldaña, Joan, 2011. "Navigation in large subway networks: An informational approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 374-386.
    26. Smyth, Russell & Mishra, Vinod & Qian, Xiaolei, 2008. "The Environment and Well-Being in Urban China," Ecological Economics, Elsevier, vol. 68(1-2), pages 547-555, December.
    27. Zhang, Jianhua & Zhao, Mingwei & Liu, Haikuan & Xu, Xiaoming, 2013. "Networked characteristics of the urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1538-1546.
    28. Laporte, G. & Mesa, J.A. & Ortega, F.A. & Perea, F., 2011. "Planning rapid transit networks," Socio-Economic Planning Sciences, Elsevier, vol. 45(3), pages 95-104, September.
    29. Zong, Fang & Tian, Yongda & He, Yanan & Tang, Jinjun & Lv, Jianyu, 2019. "Trip destination prediction based on multi-day GPS data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 258-269.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fan, Bing & Tan, Hongtao & Li, Yaqun, 2023. "Critical link identification algorithm for power communication networks in SDN architecture," International Journal of Critical Infrastructure Protection, Elsevier, vol. 40(C).
    2. Tang, Jinjun & Li, Zhitao & Gao, Fan & Zong, Fang, 2021. "Identifying critical metro stations in multiplex network based on D–S evidence theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    3. Zeng, Jie & Xiong, Yong & Liu, Feiyang & Ye, Junqing & Tang, Jinjun, 2022. "Uncovering the spatiotemporal patterns of traffic congestion from large-scale trajectory data: A complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    4. Jinjun Tang & Xiaolu Wang & Fang Zong & Zheng Hu, 2020. "Uncovering Spatio-temporal Travel Patterns Using a Tensor-based Model from Metro Smart Card Data in Shenzhen, China," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    5. Suo Qi & Wang Liyuan & Yao Tianzi & Wang Zihao, 2021. "Promoting Metro Operation Safety by Exploring Metro Operation Accident Network," Journal of Systems Science and Information, De Gruyter, vol. 9(4), pages 455-468, August.
    6. Kopsidas, Athanasios & Kepaptsoglou, Konstantinos, 2022. "Identification of critical stations in a Metro System: A substitute complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    7. Yangyang Meng & Qingjie Qi & Jianzhong Liu & Wei Zhou, 2022. "Dynamic Evolution Analysis of Complex Topology and Node Importance in Shenzhen Metro Network from 2004 to 2021," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    8. Wang, Ying & Zheng, Yunan & Shi, Xuelei & Liu, Yiguang, 2022. "An effective heuristic clustering algorithm for mining multiple critical nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    9. Wang, Ning & Gao, Ying & He, Jia-tao & Yang, Jun, 2022. "Robustness evaluation of the air cargo network considering node importance and attack cost," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    10. Ting Chen & Jianxiao Ma & Zhenjun Zhu & Xiucheng Guo, 2023. "Evaluation Method for Node Importance of Urban Rail Network Considering Traffic Characteristics," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    11. Li, Zhitao & Tang, Jinjun & Zhao, Chuyun & Gao, Fan, 2023. "Improved centrality measure based on the adapted PageRank algorithm for urban transportation multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    12. Wang, Wenhao & Wang, Yanhui & Wang, Guangxing & Li, Man & Jia, Limin, 2023. "Identification of the critical accident causative factors in the urban rail transit system by complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    13. Meng, Yangyang & Tian, Xiangliang & Li, Zhongwen & Zhou, Wei & Zhou, Zhijie & Zhong, Maohua, 2020. "Exploring node importance evolution of weighted complex networks in urban rail transit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    14. Baofeng Sun & Jiaojiao Liu & Junyi Hao & Xiuxiu Shen & Xinhua Mao & Xianmin Song, 2020. "Maintenance Decision-Making of an Urban Rail Transit System in a Regionalized Network-Wide Perspective," Sustainability, MDPI, vol. 12(22), pages 1-21, November.
    15. Shen, Jingwei & Zong, Huiming, 2023. "Identification of critical transportation cities in the multimodal transportation network of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    16. Feng, Liuyang & Zhang, Limao, 2021. "Assessment of tunnel face stability subjected to an adjacent tunnel," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    17. Zhao, Jie & Wang, Yunchuan & Deng, Yong, 2020. "Identifying influential nodes in complex networks from global perspective," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    18. Zhang, Yin-Ting & Zhou, Wei-Xing, 2023. "Quantifying the status of economies in international crop trade networks: A correlation structure analysis of various node-ranking metrics," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    19. Ma, Min & Hu, Dawei & Chien, Steven I-Jy & Liu, Jie & Yang, Xing & Ma, Zhuanglin, 2022. "Evolution assessment of urban rail transit networks: A case study of Xi’an, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    20. Wang, Longjian & Zheng, Shaoya & Wang, Yonggang & Wang, Longfei, 2021. "Identification of critical nodes in multimodal transportation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    21. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    22. Chen, Junlan & Pu, Ziyuan & Guo, Xiucheng & Cao, Jieyu & Zhang, Fang, 2023. "Multiperiod metro timetable optimization based on the complex network and dynamic travel demand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Jianhua & Wang, Shuliang & Wang, Xiaoyuan, 2018. "Comparison analysis on vulnerability of metro networks based on complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 72-78.
    2. Zhang, Jianhua & Zhao, Mingwei & Liu, Haikuan & Xu, Xiaoming, 2013. "Networked characteristics of the urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1538-1546.
    3. Zhang, Jianhua & Song, Bo & Zhang, Zhaojun & Liu, Haikuan, 2014. "An approach for modeling vulnerability of the network of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 127-136.
    4. Lin Zhang & Jian Lu & Bai-bai Fu & Shu-bin Li, 2018. "A Review and Prospect for the Complexity and Resilience of Urban Public Transit Network Based on Complex Network Theory," Complexity, Hindawi, vol. 2018, pages 1-36, December.
    5. Zhang, Yanjie & Ayyub, Bilal M. & Saadat, Yalda & Zhang, Dongming & Huang, Hongwei, 2020. "A double-weighted vulnerability assessment model for metrorail transit networks and its application in Shanghai metro," International Journal of Critical Infrastructure Protection, Elsevier, vol. 29(C).
    6. Zhang, Jianhua & Wang, Shuliang & Zhang, Zhaojun & Zou, Kuansheng & Shu, Zhan, 2016. "Characteristics on hub networks of urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 502-507.
    7. Yin, Dezhi & Huang, Wencheng & Shuai, Bin & Liu, Hongyi & Zhang, Yue, 2022. "Structural characteristics analysis and cascading failure impact analysis of urban rail transit network: From the perspective of multi-layer network," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    8. Hui Xu & Liudan Jiao & Shulin Chen & Milan Deng & Ningxin Shen, 2018. "An Innovative Approach to Determining High-Risk Nodes in a Complex Urban Rail Transit Station: A Perspective of Promoting Urban Sustainability," Sustainability, MDPI, vol. 10(7), pages 1-17, July.
    9. Zhang, Jianhua & Wang, Meng, 2019. "Transportation functionality vulnerability of urban rail transit networks based on movingblock: The case of Nanjing metro," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    10. Rui Ding & Norsidah Ujang & Hussain Bin Hamid & Mohd Shahrudin Abd Manan & Rong Li & Safwan Subhi Mousa Albadareen & Ashkan Nochian & Jianjun Wu, 2019. "Application of Complex Networks Theory in Urban Traffic Network Researches," Networks and Spatial Economics, Springer, vol. 19(4), pages 1281-1317, December.
    11. Yi Shen & Gang Ren & Bin Ran, 2021. "Cascading failure analysis and robustness optimization of metro networks based on coupled map lattices: a case study of Nanjing, China," Transportation, Springer, vol. 48(2), pages 537-553, April.
    12. Yingying Xing & Jian Lu & Shendi Chen, 2016. "Weighted Complex Network Analysis of Shanghai Rail Transit System," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-8, August.
    13. Tang, Jinjun & Hu, Jin & Hao, Wei & Chen, Xinqiang & Qi, Yong, 2020. "Markov Chains based route travel time estimation considering link spatio-temporal correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    14. Junjie Fu & Xinqiang Chen & Shubo Wu & Chaojian Shi & Huafeng Wu & Jiansen Zhao & Pengwen Xiong, 2020. "Mining ship deficiency correlations from historical port state control (PSC) inspection data," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-19, February.
    15. Zhang, Lin & Lu, Jian & Fu, Bai-bai & Li, Shu-bin, 2019. "A cascading failures model of weighted bus transit route network under route failure perspective considering link prediction effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1315-1330.
    16. Tang, Jinjun & Bi, Wei & Liu, Fang & Zhang, Wenhui, 2021. "Exploring urban travel patterns using density-based clustering with multi-attributes from large-scaled vehicle trajectories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    17. Yang, Zhijie & Chen, Xiaolong, 2018. "Evolution assessment of Shanghai Urban Rail Transit Network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1263-1274.
    18. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    19. Yangyang Meng & Qingjie Qi & Jianzhong Liu & Wei Zhou, 2022. "Dynamic Evolution Analysis of Complex Topology and Node Importance in Shenzhen Metro Network from 2004 to 2021," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    20. Jin, Kun & Wang, Wei & Li, Xinran & Hua, Xuedong & Qin, Shaoyang, 2022. "Exploring the robustness of public transportation system on augmented network: A case from Nanjing China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:539:y:2020:i:c:s0378437119316590. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.