Exploring evolutionary features of directed weighted hazard network in the subway construction

被引:11
|
作者
Hou, Gong-Yu [1 ,2 ]
Jin, Cong [1 ]
Xu, Zhe-Dong [1 ]
Yu, Ping [1 ]
Cao, Yi-Yi [1 ]
机构
[1] China Univ Min & Technol, Sch Mech & Civil Engn, Beijing 100083, Peoples R China
[2] Xinjiang Inst Engn, Sch Min Engn & Geol, Urumqi 830091, Peoples R China
基金
中国国家自然科学基金;
关键词
accident analysis; directed weighted network; complex network; evolutionary features; FUZZY-BAYESIAN NETWORK; METRO CONSTRUCTION; SAFETY; ACCIDENT; SYSTEM; PREDICTION; ACCIMAP; HFACS;
D O I
10.1088/1674-1056/28/3/038901
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
A better understanding of previous accidents is an effective way to reduce the occurrence of similar accidents in the future. In this paper, a complex network approach is adopted to construct a directed weighted hazard network (DWHN) to analyze topological features and evolution of accidents in the subway construction. The nodes are hazards and accidents, the edges are multiple relationships of these nodes and the weight of edges are occurrence times of repetitive relationships. The results indicate that the DWHN possesses the property of small-world with small average path length and large clustering coefficient, indicating that hazards have better connectivity and will spread widely and quickly in the network. Moreover, the DWHN has the property of scale-free network for the cumulative degree distribution follows a power-law distribution. It makes DWHN more vulnerable to target attacks. Controlling key nodes with higher degree, strength and betweenness centrality will destroy the connectivity of DWHN and mitigate the spreading of accidents in the network. This study is helpful for discovering inner relationships and evolutionary features of hazards and accidents in the subway construction.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Average trapping time on weighted directed Koch network
    Wu, Zikai
    Gao, Yu
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [22] A network Poisson model for weighted directed networks with covariates
    Xu, Meng
    Wang, Qiuping
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2023, 52 (15) : 5274 - 5293
  • [23] DEGREE AND WEIGHTED PROPERTIES OF THE DIRECTED CHINA RAILWAY NETWORK
    Guo, Long
    Cai, Xu
    INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2008, 19 (12): : 1909 - 1918
  • [24] Almost decouplability of any directed weighted network topology
    Cai, Ning
    Cao, Jun-Wei
    Khan, M. Junaid
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2015, 436 : 637 - 645
  • [25] Average trapping time on weighted directed Koch network
    Zikai Wu
    Yu Gao
    Scientific Reports, 9
  • [26] Condensation transitions in a model for a directed network with weighted links
    Angel, AG
    Hanney, T
    Evans, MR
    PHYSICAL REVIEW E, 2006, 73 (01)
  • [27] Weighted complex network analysis of the Beijing subway system: Train and passenger flows
    Feng, Jia
    Li, Xiamiao
    Mao, Baohua
    Xu, Qi
    Bai, Yun
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2017, 474 : 213 - 223
  • [28] Mitigating subway construction collapse risk using Bayesian network modeling
    Zhou, Zhipeng
    Liu, Song
    Qi, Haonan
    AUTOMATION IN CONSTRUCTION, 2022, 143
  • [29] Exploring the Moral Hazard Evolutionary Mechanism for BIM Implementation in an Integrated Project Team
    Du, Yanchao
    Zhou, Hengyu
    Yuan, Yongbo
    Xue, Hong
    SUSTAINABILITY, 2019, 11 (20)
  • [30] Guidelines for exploring construction sites in virtual reality environments for hazard identification
    Lucena, Arthur Felipe Echs
    Saffaro, Fernanda Aranha
    INTERNATIONAL JOURNAL OF OCCUPATIONAL SAFETY AND ERGONOMICS, 2022, 28 (01) : 86 - 95