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Identifying hub stations and important lines of bus networks: A case study in Xiamen, China

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  • Zhang, Hui
  • Zhuge, Chengxiang
  • Yu, Xiaohua

Abstract

Hub stations and important lines play key roles in transfers between stations. In this paper, a node failure model is proposed to identify hub stations. In the model, we introduce two new indicators called neighborhood degree ratio and transfer index to evaluate the importance of stations, which consider neighborhood stations’ degree of station and the initial transfer times between stations. Moreover, line accessibility is developed to measure the importance of lines in the bus network. Xiamen bus network in 2016 is utilized to test the model. The results show that the two introduced indicators are more effective to identify hub stations compared with traditional complex network indicators such as degree, clustering coefficient and betweenness.

Suggested Citation

  • Zhang, Hui & Zhuge, Chengxiang & Yu, Xiaohua, 2018. "Identifying hub stations and important lines of bus networks: A case study in Xiamen, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 394-402.
    • Handle: RePEc:eee:phsmap:v:502:y:2018:i:c:p:394-402
    DOI: 10.1016/j.physa.2018.02.182
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    3. Wang, Min & Cheng, Qing & Huang, Jincai & Cheng, Guangquan, 2021. "Research on optimal hub location of agricultural product transportation network based on hierarchical hub-and-spoke network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    4. Abdelaty, Hatem & Mohamed, Moataz & Ezzeldin, Mohamed & El-Dakhakhni, Wael, 2022. "Temporal robustness assessment framework for city-scale bus transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    5. Jianmin Jia & Chenhui Liu & Tao Wan, 2019. "Planning of the Charging Station for Electric Vehicles Utilizing Cellular Signaling Data," Sustainability, MDPI, vol. 11(3), pages 1-16, January.
    6. Zhang, Hui & Cui, Houdun & Wang, Wei & Song, Wenbo, 2020. "Properties of Chinese railway network: Multilayer structures based on timetable data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    7. 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.

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