Shandong Science ›› 2024, Vol. 37 ›› Issue (4): 105-111.doi: 10.3976/j.issn.1002-4026.20230093

• Traffic and Transportation • Previous Articles     Next Articles

Durability and resilience of Nanjing Rail Transit Network

GAO Zhanyi1(), ZHU Chengjuan1,2,*(), HAN Linghui2   

  1. 1. School of Traffic and Transportation Engineering,Dalian Jiaotong University, Dalian 116028,China
    2. School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026,China
  • Received:2023-06-05 Online:2024-08-20 Published:2024-08-05
  • Contact: ZHU Chengjuan E-mail:gaozhanyi2021@163.com;cjzhu@djtu.edu.cn

Abstract:

This study first constructs a topological structure model of the rail transit network based on the Space L network topology method. Herein, upon analyzing network characteristics using UCINET as a basis, the maximum connected subgraph ratio and overall network efficiency are selected as indicators to analyze the resilience of the rail transit network. Then, the article comprehensively analyzes the attribute values of nodes and employs the TOPSIS method to rank the importance of nodes using the coefficient of variation for weighting. Then network resilience is analyzed by destroying individual nodes with high importance, and network recovery is achieved through indicator-based ranking restoration strategies, ultimately yielding the average resilience value of the rail transit network. Furthermore, the resilience and robustness of the rail transit network of Nanjing in 2022 is analyzed based on the established model. Results show that nodes with high degree values often have a greater impact on resilience than other indicators. Prioritizing the repair of nodes with the highest degree values leads to the greatest increase in network efficiency, whereas repairing nodes with the highest closeness to the center has less impact on network efficiency.

Key words: complex networks, evaluation model, resistance to destruction, network resilience, recovery strategy, the largest connected subgraph, network efficiency

CLC Number: 

  • U121