Cause analysis of ship collision accident based on complex network theory

Abstract

To determine the relationship between various factors leading to ship collision accidents and prevent ship collision accidents. This paper collected 100 reports of ship collision accidents, and 40 causative factors were determined from the four aspects of human, ship, environment, and management. The relationship among 136 kinds of causation factors was determined by extracting the causation chain from the accident report, and the causation network model of ship collision accidents was established. Python simulation was used to analyze the robustness of the causative network under deliberate and random attacks. By comparing the robustness of the causative network under degree value attack, betweenness centrality value attack, closeness centrality value attack, and PR value attack, the key factors in the causative network were identified, and corresponding prevention strategies were proposed. The simulation results show that the robustness of the causative network is weak under the deliberate attack, the robustness of the betweenness centrality value attack is the worst, and the node with a higher betweenness centrality value is the key node in the causal network, giving priority to the prevention of key nodes is conducive to the safe navigation of ships.