Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics
AbstractAccidents occur frequently in traffic-intensive waters, which restrict the safe and rapid development of the shipping industry. Due to the suddenness, randomness, and uncertainty of accidents in traffic-intensive waters, the probability of the risk factors causing traffic accidents is usually high. Thus, properly analyzing those key risk factors is of great significance to improve the safety of shipping. Based on the analysis of influencing factors of ship navigational risks in traffic-intensive waters, this paper proposes a cloud model to excavate the factors affecting navigational risk, which could accurately screen out the key risk factors. Furthermore, the risk causal model of ship navigation in traffic-intensive waters is constructed by using the infectious disease dynamics method in order to model the key risk causal transmission process. Moreover, an empirical study of the Yangtze River estuary is conducted to illustrate the feasibility of the proposed models. The research results show that the cloud model is useful in screening the key risk factors, and the constructed causal model of ship navigational risks in traffic-intensive waters is able to provide accurate analysis of the transmission process of key risk factors, which can be used to reduce the navigational risk of ships in traffic-intensive waters. This research provides both theoretical basis and practical reference for regulators in the risk management and control of ships in traffic-intensive waters. View Full-Text
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Chen, Y.-J.; Liu, Q.; Wan, C.-P. Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics. J. Mar. Sci. Eng. 2019, 7, 277.
Chen Y-J, Liu Q, Wan C-P. Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics. Journal of Marine Science and Engineering. 2019; 7(8):277.Chicago/Turabian Style
Chen, Yong-jun; Liu, Qing; Wan, Cheng-peng. 2019. "Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics." J. Mar. Sci. Eng. 7, no. 8: 277.
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