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A cascading failures model of weighted bus transit route network under route failure perspective considering link prediction effect

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  • Zhang, Lin
  • Lu, Jian
  • Fu, Bai-bai
  • Li, Shu-bin

Abstract

To fulfill the missing part in cascading failures based reliability study of bus transit network (BTN), this paper is devoted to establishing a novel cascading failures model under route failure perspective, as well as considering the link prediction effect on failure load dynamic redistribution (FLDR). First, for advancing the route failure perspective, the weighted bus transit route network (weighted BTRN) is established through modifying the Space R method. Thereby, the represented passenger flow system of BTN can adapt to the demand of investigating the cascading failures under route failure perspective, because the node actually denotes the route under weighted BTRN perspective. Second, through analyzing the general evolution process of FLDR under time step scale perspective and providing the overall evolution steps of the proposed cascading failures model, the cascading failures analytical framework under time step scale perspective is further proposed. Furthermore, through embedding the effect of structural similarity based link prediction indices on evaluating the existence possibility relative size of all optional evacuation links, FLDR pattern considering link prediction effect is proposed. Finally, the case study of Jinan’s BTRN is conducted to verify the adaptability of the proposed cascading failures model. This interdisciplinary study between transportation engineering and system science provides a strong link between two important study areas of complex network theory- cascading failures and link prediction, and helps to improve the engineering applicability of cascading failures based reliability model in actual BTN operation.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:523:y:2019:i:c:p:1315-1330
    DOI: 10.1016/j.physa.2019.04.122
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    3. Jin, Kun & Wang, Wei & Li, Xinran & Chen, Siyuan & Qin, Shaoyang & Hua, Xuedong, 2023. "Cascading failure in urban rail transit network considering demand variation and time delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
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    7. Yang, Qihui & Scoglio, Caterina M. & Gruenbacher, Don M., 2021. "Robustness of supply chain networks against underload cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).

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