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Chin. Phys. B, 2022, Vol. 31(6): 068905    DOI: 10.1088/1674-1056/ac4a6c

Analysis of identification methods of key nodes in transportation network

Qiang Lai(赖强) and Hong-Hao Zhang(张宏昊)
School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China
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.
Keywords:  transportation network      key node identification      KSD identification method      network efficiency  
Received:  04 December 2021      Revised:  31 December 2021      Accepted manuscript online:  12 January 2022
PACS:  89.75.Fb (Structures and organization in complex systems)  
Fund: 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).
Corresponding Authors:  Qiang Lai     E-mail:

Cite this article: 

Qiang Lai(赖强) and Hong-Hao Zhang(张宏昊) Analysis of identification methods of key nodes in transportation network 2022 Chin. Phys. B 31 068905

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