中国安全科学学报 ›› 2025, Vol. 35 ›› Issue (5): 229-236.doi: 10.16265/j.cnki.issn1003-3033.2025.05.1144

• 公共安全 • 上一篇    下一篇

改进LeaderRank算法下高原山区公路网络关键节点识别

何云勇1(), 何恩怀1, 陈治宇1,**(), 高建平2, 张乐1, 孙璐1   

  1. 1 四川省公路规划勘察设计研究院有限公司,四川 成都 610041
    2 重庆交通大学 土木工程学院,重庆 400041
  • 收稿日期:2024-12-16 修回日期:2025-02-14 出版日期:2025-05-28
  • 通信作者:
    ** 陈治宇(1998—),男,重庆人,硕士,助理工程师,主要从事道路工程方面的工作。E-mail:
  • 作者简介:

    何云勇 (1986—),男,四川广安人,博士,正高级工程师,主要从事道路工程方面的工作。E-mail:

    何云勇, 正高级工程师

    何恩怀, 正高级工程师

    高建平, 教授

    张乐, 工程师

    孙璐, 正高级工程师

  • 基金资助:
    四川省交通运输科技项目(2025-A-09); 四川省交通运输科技项目(2022-A-01)

Key node recognition of highway network in high altitude mountainous area based on improved LeaderRank algorithm

HE Yunyong1(), HE Enhuai1, CHEN Zhiyu1,**(), GAO Jianping2, ZHANG Le1, SUN Lu1   

  1. 1 Sichuan Highway Planning, Survey, Design and Research Institute Ltd., Chengdu Sichuan 610041, China
    2 School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
  • Received:2024-12-16 Revised:2025-02-14 Published:2025-05-28

摘要: 为提升高原山区公路网络的稳定性和安全性,选取度中心性、中介中心性、接近中心性、行程时间权值和邻接节点通行时间度5项指标,建立关键节点评价指标体系,提出一种综合考虑拓扑结构和交通功能的关键节点识别方法,并以四川西部高原山区公路为例,在无向加权网络框架中,探究改进LeaderRank、PageRank和度中心性3种算法的关键节点识别效果与节点失效情况下网络效率和连通率的变化差异性。结果表明:3种算法在节点的关键程度上展现出不同优先级;按照改进LeaderRank算法排序的节点失效时,网络效率与连通率的下降最为迅速,且下降幅度也更为显著。

关键词: 改进LeaderRank, 高原山区公路, 网络关键节点, 节点重要性, 复杂网络

Abstract:

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 ide.pngication 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 ide.pngying 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.

Key words: improved LeaderRank, highway in plateau mountain area, network key node, node importance, complex network

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