摘要
为探究船舶在大风浪中发生倾覆的原因,利用贝叶斯网络建立船舶倾覆模型,分析我国2005—2019年船舶在大风浪中的倾覆事故。结合数据样本,从人、船、环境、管理四个方面对造成倾覆事故的原因进行分析,确定网络节点,进而找到每起倾覆事故的事故链,并建立大风浪中船舶倾覆事故的贝叶斯网络。通过Netica软件对所建立的贝叶斯网络进行分析,找出船舶在大风浪中倾覆的致因链。结果表明:该贝叶斯网络能够利用船舶航行时的信息预测出船舶在大风浪中发生倾覆的概率,可为航运公司及船员在大风浪下的操纵提供建议,对保障船舶在大风浪中的安全航行具有一定的实际意义。
In order to explore the causes of ship capsizing accidents in heavy winds and waves,the ship capsizing model is established by the Bayesian network to analyze the ship capsizing accidents in heavy winds and waves in China from 2005 to 2019.Combining with data samples,the causes of the capsizing accidents are analyzed from four aspects of human,ships,environment and management,the network nodes are determined,then the accident chain of each capsizing accident is found,and the Bayesian network of ship capsizing accidents in heavy winds and waves is established.The Bayesian network is analyzed by Netica software to find out the causation chain of ship capsizing accidents in heavy winds and waves.The result shows that,the Bayesian network can predict the probability of ship capsizing accidents in heavy winds and waves using the information of ship sailing,which can provide suggestions for shipping companies and crew for ship manoeuvring in heavy winds and waves.It has certain practical significance to ensure the ship safe navigation in heavy winds and waves.
作者
刘子涛
杜柏松
贾帅林
LIU Zitao;DU Baisong;JIA Shuailin(School of Naval Architecture and Maritime,Zhejiang Ocean University,Zhoushan 316022,Zhejiang,China)
出处
《上海海事大学学报》
北大核心
2022年第3期56-61,共6页
Journal of Shanghai Maritime University
基金
浙江海洋大学大学生科技创新项目(20200922)
浙江海洋大学研究生教育质量工程案例库建设项目(111810641211)。
关键词
贝叶斯网络
概率推理
大风浪
船舶倾覆
Bayesian network
probabilistic inference
heavy winds and waves
ship capsizing
