Development of an improved Bayesian network method for maritime accident safety assessment based on multiscale scenario analysis theory

Dewei Kong, Zelong Lin, Wei Li and Wei He

Reliability Engineering and System Safety, 2024, vol. 251, issue C

Abstract: The strait is infrastructure for connecting ports, ensuring the national economy and human life. Assessing maritime safety is crucial for strait operation and maintenance. Current methods over-rely on statistical analysis of historical data, which lacks scientific algorithms and cannot accurately assess safety timeliness. Therefore, this study proposes an improved Bayesian network (BN) model based on the multiscale scenario analysis theory to process to the maritime safety assessment process. Firstly, the maritime safety assessment model is constructed based on the knowledge element theory (KET) and scenario analysis theory (SAT). Secondly, a heuristic learning algorithm is used to construct the BN model of maritime accidents to define scenario elements and key parameters. Thirdly, a scenario simulation is conducted with the Bohai Strait as a case to assessment its emergency capability in catastrophic accidents. This paper successfully developed a maritime accident safety assessment framework using an improved BN algorithm within a scenario analysis perspective, significantly enhancing the accuracy and reliability of safety assessments. This methodology used in this study can be used a tool suitable for the safety assessment of major infrastructure accidents at the national level and the results obtained can serve as a reference for dynamically revising emergency plans.

Keywords: Maritime safety; Safety assessment; Scenario analysis theory; Improved Bayesian network; Integrated management (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:251:y:2024:i:c:s0951832024004162

DOI: 10.1016/j.ress.2024.110344

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