Analysis of identification methods of key nodes in transportation network

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 meth...

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Veröffentlicht in:Chinese physics B 2022-06, Vol.31 (6), p.68905-897
Hauptverfasser: Lai, Qiang, Zhang, Hong-Hao
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description 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.
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B</addtitle><description>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. 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subjects key node identification
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network efficiency
transportation network
title Analysis of identification methods of key nodes in transportation network
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