By analyzing the collected accident reports of ship grounding incidents, our aim is to summarize the primary human factors that lead to ship groundings. Through an analysis of the causal chain of grounding accidents, we will determine the Bayesian network structure. Finally, we will apply accident samples to validate the effectiveness of the Bayesian network model established in this paper. Simultaneously, we will conduct a causal analysis of the Bayesian network model to identify the most probable causal chain leading to grounding accidents, thereby providing safety management strategies for seafarers, shipping companies, and maritime safety regulatory authorities.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Analysis of human factors in ship grounding accidents based on Bayesian networks


    Beteiligte:
    Shangguan, Wei (Herausgeber:in) / Wu, Jianqing (Herausgeber:in) / Wang, Xiaoshuai (Autor:in) / Wang, Fengwu (Autor:in) / Ji, Zhe (Autor:in)

    Kongress:

    Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023) ; 2023 ; Xi'an, China


    Erschienen in:

    Proc. SPIE ; 12989


    Erscheinungsdatum :

    09.04.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Theoretical and statistical analysis of ship grounding accidents

    Simonsen, B.C. / Hansen, P.F. | Tema Archiv | 2000


    Research on human factors of ship grounding accident based on HFACS

    Wang, Xiaoshuai / Wang, Fengwu / Zhang, Zhirui et al. | IEEE | 2023


    Analysis of Factors Influencing Road Traffic Accidents’ Severity Based on Bayesian Networks

    Wei, Panyi / Huang, Jianling / Chen, Yanyan et al. | ASCE | 2022


    Analysis of Factors Influencing Road Traffic Accidents’ Severitv Based on Bayesian Networks

    Wei, Panyi / Huang, Jianling / Chen, Yanyan et al. | TIBKAT | 2022