@article{11cb3611b63741dcb6581a2cd23b90e5,
title = "A novel emergency decision-making model for collision accidents in the Yangtze River",
abstract = "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.",
keywords = "Bayesian network, Collision accidents, Decision-making, Maritime safety",
author = "Bing Wu and Congcong Zhao and Yip, {Tsz Leung} and Dan Jiang",
note = "Funding Information: The research presented in this paper was sponsored by a grant from National Key Technologies Research & Development Program (grant number 2019YFB1600600; 2019YFB1600603), National Natural Science Foundation of China (Grant No. 51809206), International?Cooperation?and?Exchange?of?the National Natural?Science?Foundation of China (Grant No.51920105014), Shenzhen Science and Technology Innovation Committee (Grant No. CJGJZD20200617102602006) and the Hong Kong Scholar Program (No.2017XJ064). Funding Information: The research presented in this paper was sponsored by a grant from National Key Technologies Research & Development Program (grant number 2019YFB1600600 ; 2019YFB1600603 ), National Natural Science Foundation of China (Grant No. 51809206 ), International Cooperation and Exchange of the National Natural Science Foundation of China (Grant No. 51920105014 ), Shenzhen Science and Technology Innovation Committee (Grant No. CJGJZD20200617102602006 ) and the Hong Kong Scholar Program (No. 2017XJ064 ). Publisher Copyright: {\textcopyright} 2021 Elsevier Ltd Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2021",
month = mar,
day = "1",
doi = "10.1016/j.oceaneng.2021.108622",
language = "English",
volume = "223",
journal = "Ocean Engineering",
issn = "0029-8018",
publisher = "Elsevier B.V.",
}