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Node importance identification of unweighted urban rail transit network: An Adjacency Information Entropy based approach

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  • Huang, Wencheng
  • Li, Haoran
  • Yin, Yanhui
  • Zhang, Zhi
  • Xie, Anhao
  • Zhang, Yin
  • Cheng, Guo

Abstract

Inspiring by the theory of degree entropy, and considering both the location of the evaluated node and its neighboring nodes in an unweighted urban rail transit network (URTN), a new node identification approach called Adjacency Information Entropy (AIE) is applied to identify the importance of node in URTN. An undirected and unweighted network, a single-way directed and unweighted network, and a double-way directed and unweighted network are constructed as the background of the numerical study, some other previous approaches are used as the comparison algorithms. Finally, based on the double-way directed and unweighted network topology of Chengdu Metro, a real-world case study is conducted. We find that: (i) For a node in a directed and unweighted network, as long as the in-degree and out-degree of a node are not both 0, then the node can be identified based on AIE. (ii) For a double-way directed and unweighted network, if a node has higher node degree and higher Adjacency Degree, then it is more important in the network. (iii) If a node has high AIE in the entire topology of URTN, then it generates connections among non-adjacent nodes.

Suggested Citation

  • Huang, Wencheng & Li, Haoran & Yin, Yanhui & Zhang, Zhi & Xie, Anhao & Zhang, Yin & Cheng, Guo, 2024. "Node importance identification of unweighted urban rail transit network: An Adjacency Information Entropy based approach," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    • Handle: RePEc:eee:reensy:v:242:y:2024:i:c:s0951832023006804
    DOI: 10.1016/j.ress.2023.109766
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