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Key node recognition of highway network in high altitude mountainous area based on improved LeaderRank algorithm
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Yunyong HE1, Enhuai HE1, Zhiyu CHEN**, 1, Jianping GAO2, Le ZHANG1, Lu SUN1
China Safety Science Journal | 2025, 35(5) : 229 - 236
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China Safety Science Journal | 2025, 35(5): 229-236
• Public safety •
Key node recognition of highway network in high altitude mountainous area based on improved LeaderRank algorithm
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Yunyong HE1, Enhuai HE1, Zhiyu CHEN**, 1, Jianping GAO2, Le ZHANG1, Lu SUN1
Affiliations
  • 1Sichuan Highway Planning, Survey, Design and Research Institute Ltd., Chengdu Sichuan 610041, China
  • 2School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Published: 2025-05-28 doi: 10.16265/j.cnki.issn1003-3033.2025.05.1144
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To improve the stability and safety of highway networks in plateau mountainous areas, an evaluation index system for critical nodes was established by selecting five indicators: degree centrality, betweenness centrality, closeness centrality, travel time weight, and adjacent node travel time degree. A critical node identification method integrating topological structure and traffic functionality was proposed. Taking the highway network in western Sichuan Plateau mountainous region as a case study, the differential performance of three improved algorithms was investigated. This algorithms included modified LeaderRank, PageRank, and degree centrality. Their performance was examined in identifying critical nodes within an undirected weighted network framework. Additionally, the variations in network efficiency and connectivity rate under node failure scenarios were systematically examined. The results demonstrate that the three algorithms exhibit distinct prioritization in assessing node criticality. Node failure sequences ranked by the modified LeaderRank algorithm induce the most rapid and significant decline in both network efficiency and connectivity rate.

improved LeaderRank  /  highway in plateau mountain area  /  network key node  /  node importance  /  complex network
Yunyong HE, Enhuai HE, Zhiyu CHEN, Jianping GAO, Le ZHANG, Lu SUN. Key node recognition of highway network in high altitude mountainous area based on improved LeaderRank algorithm[J]. China Safety Science Journal, 2025 , 35 (5) : 229 -236 . DOI: 10.16265/j.cnki.issn1003-3033.2025.05.1144
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Year 2025 volume 35 Issue 5
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2025.05.1144
  • Receive Date：2024-12-16
  • Online Date：2026-07-08
  • Published：2025-05-28
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  • Received：2024-12-16
  • Revised：2025-02-14
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    1Sichuan Highway Planning, Survey, Design and Research Institute Ltd., Chengdu Sichuan 610041, China
    2School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
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