A propagation model of ship collision causation based on complex network dynamics theory

JianZhou Liu; Huaiwei Zhu; Chaoxu Yang; Li Xu; Tian Chai

doi:10.1117/12.3015820

20 February 2024 A propagation model of ship collision causation based on complex network dynamics theory

JianZhou Liu, Huaiwei Zhu, Chaoxu Yang, Li Xu, Tian Chai

Proceedings Volume 13064, Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023); 1306412 (2024) https://doi.org/10.1117/12.3015820
Event: 7th International Conference on Traffic Engineering and Transportation System (ICTETS 2023), 2023, Dalian, China

Abstract

In order to reveal the ship collision causation propagation law, a ship collision causation propagation model is proposed in this paper based on the complex network dynamics theory. The model improved the Susceptible—Infected—Recovered (SIR) model and makes it applicable to the dynamic process of risk propagation. In order to apply the model to the actual network, we construct a ship collision causation network. The network is used as the simulation object of this study. The simulation results show that the causative nodes of different importance have the ability to propagate the risk to the whole network. The impact of accident causation can be reduced by shortening the inspection time of accident causation, reducing the risk propagation rate, increasing the risk control rate, and selecting appropriate initial control factors. The model can help to simulate the propagation of the causes of ship collisions, and can quantitatively analyze the impact of the causes on ship collisions.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

JianZhou Liu, Huaiwei Zhu, Chaoxu Yang, Li Xu, and Tian Chai "A propagation model of ship collision causation based on complex network dynamics theory", Proc. SPIE 13064, Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023), 1306412 (20 February 2024); https://doi.org/10.1117/12.3015820

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