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The complexity and uncertainty of large public works systems make it of great practical significance to study the strategy selection behavior of the management subjects of safety accident prevention and control of large public works projects. Based on the complex network formed by the interaction behaviors of accident prevention and control management subjects, we introduce the learning algorithm of charisma value of empirical weights, construct the “Agent-cellular Automata” model of decision-making behaviors of management subjects in the prevention and control of construction accidents of large public engineering projects, and study the competitive evolution of risk management strategies. The results show that the risk management strategy selection of each participating subject is not only affected by its own expected benefit, but also affected by the risk management strategy selection of other heterogeneous subjects in the project, the charisma index of the strategy has a greater impact on the behavior of participating subjects, and the punishment mechanism of the strategy has a greater impact on the behavior of participating subjects. The research results provide a theoretical basis for the practical promotion and application of construction accident prevention and control management strategies in large public works projects.

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Evolutionary Analysis of the Game Behavior of Government Supervisors and Project Responsible Parties Based on the Prevention and Control of Construction Accidents in Large Public Works Projects from the Perspective of Complex Networks

  • 会议论文

  • 发表日期：

    2025年

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  • Yanyan Wen,
  • Yulong Huo,
  • Baoqi Wang,
  • Ruoqian Wang,
  • Haifeng Li

摘要

The complexity and uncertainty of large public works systems make it of great practical significance to study the strategy selection behavior of the management subjects of safety accident prevention and control of large public works projects. Based on the complex network formed by the interaction behaviors of accident prevention and control management subjects, we introduce the learning algorithm of charisma value of empirical weights, construct the “Agent-cellular Automata” model of decision-making behaviors of management subjects in the prevention and control of construction accidents of large public engineering projects, and study the competitive evolution of risk management strategies. The results show that the risk management strategy selection of each participating subject is not only affected by its own expected benefit, but also affected by the risk management strategy selection of other heterogeneous subjects in the project, the charisma index of the strategy has a greater impact on the behavior of participating subjects, and the punishment mechanism of the strategy has a greater impact on the behavior of participating subjects. The research results provide a theoretical basis for the practical promotion and application of construction accident prevention and control management strategies in large public works projects.