Data-driven Bayesian risk assessment of factors influencing the severity of marine accidents in port areas

IF 6.9 2区环境科学与生态学 Q1 ENGINEERING, CHEMICAL

Process Safety and Environmental Protection Pub Date : 2024-10-26 DOI:10.1016/j.psep.2024.10.074

Mehmet Kaptan, Ozan Bayazit

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引用次数: 0

Abstract

The most prevalent types of ship accidents in port areas are allisions, collisions, and groundings. A comprehensive risk assessment is needed to prevent and mitigate these accidents and their consequences. This study evaluates the risk of such accidents in port areas by presenting a model that elucidates the relationship between risk-identifying factors (RIFs) and accident severity. In this context, the RIFs are determined by analyszing the reports of 528 accidents that occurred in port areas between 1995 and 2023. Subsequently, the model is created by analysing the data derived from these reports using the Tree Augmented Naive Bayes (TAN) algorithm, which is an approach of the data-driven Bayesian network method. The findings of the study indicate that accident type, wind, ship age, and vessel type are the most influential factors in predicting the severity of accidents in port areas. It is thought that the model will assist port authorities in identifying operational risks contributing to accidents and in formulating preventive regulations.

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对影响港区海上事故严重性的因素进行数据驱动的贝叶斯风险评估

港区最常见的船舶事故类型是碰撞、相撞和搁浅。为了预防和减轻这些事故及其后果，需要进行全面的风险评估。本研究通过提出一个模型，阐明风险识别因素（RIFs）与事故严重性之间的关系，对港区此类事故的风险进行评估。在此背景下，通过分析 1995 年至 2023 年期间在港口地区发生的 528 起事故的报告，确定了风险识别因素。随后，利用数据驱动贝叶斯网络方法中的树状增强奈维贝叶斯（TAN）算法分析这些报告中的数据，创建模型。研究结果表明，事故类型、风力、船龄和船舶类型是预测港区事故严重程度的最有影响力的因素。据认为，该模型将有助于港口当局识别导致事故的操作风险，并制定预防性法规。

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

Process Safety and Environmental Protection 环境科学-工程：化工

CiteScore

11.40

自引率

15.40%

发文量

929

审稿时长

8.0 months

期刊介绍： The Process Safety and Environmental Protection (PSEP) journal is a leading international publication that focuses on the publication of high-quality, original research papers in the field of engineering, specifically those related to the safety of industrial processes and environmental protection. The journal encourages submissions that present new developments in safety and environmental aspects, particularly those that show how research findings can be applied in process engineering design and practice. PSEP is particularly interested in research that brings fresh perspectives to established engineering principles, identifies unsolved problems, or suggests directions for future research. The journal also values contributions that push the boundaries of traditional engineering and welcomes multidisciplinary papers. PSEP's articles are abstracted and indexed by a range of databases and services, which helps to ensure that the journal's research is accessible and recognized in the academic and professional communities. These databases include ANTE, Chemical Abstracts, Chemical Hazards in Industry, Current Contents, Elsevier Engineering Information database, Pascal Francis, Web of Science, Scopus, Engineering Information Database EnCompass LIT (Elsevier), and INSPEC. This wide coverage facilitates the dissemination of the journal's content to a global audience interested in process safety and environmental engineering.