Journal
OCEAN ENGINEERING
Volume 223, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.oceaneng.2021.108622
Keywords
Collision accidents; Decision-making; Bayesian network; Maritime safety
Funding
- National Key Technologies Research & Development Program [2019YFB1600600, 2019YFB1600603]
- National Natural Science Foundation of China [51809206]
- International Cooperation and Exchange of the National NaturalScience Foundation of China [51920105014]
- Shenzhen Science and Technology Innovation Committee [CJGJZD20200617102602006]
- Hong Kong Scholar Program [2017XJ064]
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This paper proposes a novel Bayesian Network model for emergency decision-making to reduce the consequence of ship-ship collision accidents in the Yangtze River. The model includes a three-layer decision-making framework and conditional probability tables, providing an intuitive and easy-to-implement method for dealing with incomplete and updated information in accident situations. The proposed method is applied to a typical collision accident, offering a practical and innovative decision-making approach for such incidents.
Collision accident accounts for the largest proportion among all types of maritime accidents, emergency decision-making is essential to reduce the consequence of such accidents. This paper proposes a novel Bayesian Network based emergency decision-making model for consequence reduction of individual ship-ship collision in the Yangtze River. The kernel of this method is to propose a three-layer decision-making framework, to develop the graphical structure for describing the accident process and to establish the conditional probability tables for the quantitative relationships. The merits of the proposed method include the intuitive representation of accident development, easy to implement, ability to deal with incomplete information and updated information. This proposed method is applied to a typical collision accident in the Yangtze River. Consequently, this paper provides a practical and novel decision-making method for collision accidents.
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