中国物理B ›› 2022, Vol. 31 ›› Issue (6): 68905-068905.doi: 10.1088/1674-1056/ac4a6c

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Analysis of identification methods of key nodes in transportation network

Qiang Lai(赖强)† and Hong-Hao Zhang(张宏昊)   

  1. School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China
  • 收稿日期:2021-12-04 修回日期:2021-12-31 接受日期:2022-01-12 出版日期:2022-05-17 发布日期:2022-05-26
  • 通讯作者: Qiang Lai E-mail:laiqiang87@126.com
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant No. 61961019) and the Youth Key Project of the Natural Science Foundation of Jiangxi Province of China (Grant No. 20202ACBL212003).

Analysis of identification methods of key nodes in transportation network

Qiang Lai(赖强)† and Hong-Hao Zhang(张宏昊)   

  1. School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China
  • Received:2021-12-04 Revised:2021-12-31 Accepted:2022-01-12 Online:2022-05-17 Published:2022-05-26
  • Contact: Qiang Lai E-mail:laiqiang87@126.com
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No. 61961019) and the Youth Key Project of the Natural Science Foundation of Jiangxi Province of China (Grant No. 20202ACBL212003).

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摘要： The identification of key nodes plays an important role in improving the robustness of the transportation network. For different types of transportation networks, the effect of the same identification method may be different. It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks. Based on the knowledge of complex networks, the metro networks and the bus networks are selected as the objects, and the key nodes are identified by the node degree identification method, the neighbor node degree identification method, the weighted k-shell degree neighborhood identification method (KSD), the degree k-shell identification method (DKS), and the degree k-shell neighborhood identification method (DKSN). Take the network efficiency and the largest connected subgraph as the effective indicators. The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.

关键词: transportation network, key node identification, KSD identification method, network efficiency

Abstract: The identification of key nodes plays an important role in improving the robustness of the transportation network. For different types of transportation networks, the effect of the same identification method may be different. It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks. Based on the knowledge of complex networks, the metro networks and the bus networks are selected as the objects, and the key nodes are identified by the node degree identification method, the neighbor node degree identification method, the weighted k-shell degree neighborhood identification method (KSD), the degree k-shell identification method (DKS), and the degree k-shell neighborhood identification method (DKSN). Take the network efficiency and the largest connected subgraph as the effective indicators. The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.

Key words: transportation network, key node identification, KSD identification method, network efficiency

中图分类号:  (Structures and organization in complex systems)

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