Liability division for ship collision accidents based on ontology model and bayesian network

IF 4.8 2区环境科学与生态学 Q1 OCEANOGRAPHY

Ocean & Coastal Management Pub Date : 2025-06-20 DOI:10.1016/j.ocecoaman.2025.107824

Yaqing Shu , Ao Dong , Beiyan Ye , Chengyong Liu , Langxiong Gan , Lan Song

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引用次数: 0

Abstract

With the increase in maritime transport, ship collision accidents have occurred frequently and caused serious impacts on maritime traffic safety and the environment. In this research, a new method combining the ontology model and Bayesian network is proposed to address liability division for ship collision accidents. Firstly, 241 maritime traffic accident reports were collected from the China Maritime Safety Administration (CHINA MSA) between 2018 and 2021. Then, the improved Apriori algorithm is proposed to extract strong association rules and to construct the ship collision negligence ontology based on accident reports. After that, the liability division model is obtained by the ontology mapping Bayesian network and the maximum likelihood estimation method is used for parameter learning for this model. Finally, the proposed method is verified using sample data from the accident reports. The results showed a good capability of liability division for ship collision accidents of the proposed model. This method could serve as a powerful tool for liability division for ship collision accidents in maritime traffic.

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基于本体模型和贝叶斯网络的船舶碰撞事故责任划分

随着海上运输量的增加，船舶碰撞事故频繁发生，对海上交通安全和环境造成了严重影响。本研究提出了一种将本体模型与贝叶斯网络相结合的船舶碰撞事故责任划分方法。首先，从中国海事局（China MSA）收集了2018年至2021年期间的241起海上交通事故报告。然后，提出改进的Apriori算法提取强关联规则，构建基于事故报告的船舶碰撞过失本体；然后，利用本体映射贝叶斯网络得到责任划分模型，并利用极大似然估计方法对该模型进行参数学习。最后，用事故报告中的样本数据对所提方法进行了验证。结果表明，该模型对船舶碰撞事故具有较好的责任划分能力。该方法可作为海上交通船舶碰撞事故责任划分的有力工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Ocean & Coastal Management 环境科学-海洋学

CiteScore

8.50

自引率

15.20%

发文量

321

审稿时长

60 days

期刊介绍： Ocean & Coastal Management is the leading international journal dedicated to the study of all aspects of ocean and coastal management from the global to local levels. We publish rigorously peer-reviewed manuscripts from all disciplines, and inter-/trans-disciplinary and co-designed research, but all submissions must make clear the relevance to management and/or governance issues relevant to the sustainable development and conservation of oceans and coasts. Comparative studies (from sub-national to trans-national cases, and other management / policy arenas) are encouraged, as are studies that critically assess current management practices and governance approaches. Submissions involving robust analysis, development of theory, and improvement of management practice are especially welcome.