Vessel incidents periodically occur in the waterways of the United States, but some types of commercial vessels have shown a downward trend in the number of incidents in recent years. One of the missions of the United States Coast Guard (USCG) is to develop regulations to mitigate and potentially prevent maritime incidents. In this paper, the USCG gathered data on more than 117,000 incidents that involved U.S.-flag vessels in U.S. waterways for the period 2001 through 2018. We applied the Grey System theory or model and Grey-Markov forecasting model to predict the future number of vessel incidents for four different vessel types from 2019 through 2030. Incident data can vary considerably from year to year and often can be incomplete. The Grey-Markov model, which is a combination of the Grey model and the Markov chain process, is suitable for this purpose because of its predictive ability. From our results, we found that the Grey-Markov model performed exceptionally well and showed the predicted values of the number of incidents to be remarkably similar to the actual values with acceptable mean relative errors ranging from 5.2% to 8.2%. We expect that these results will benefit decision makers in formulating sound policies thereby improving the maritime safety of vessels operating in waterways of the United States.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Forecasting U.S. Maritime Incidents using the Grey-Markov Model


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Zouhair, Fatima (Autor:in) / Kerby, Jerome (Autor:in)


    Erscheinungsdatum :

    04.04.2021




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Traffic Accidents Prediction Using Improved Grey-Markov Model

    Chen, Kuan Min ;Xie, Lai Fa ;Xiang, Wen Sen | Trans Tech Publications | 2011


    Incidents At Sea Agreement and Maritime Confidence-Building Measures

    Weeks, S. B. / Council for Security Cooperation in the Asia Pacific; Maritime Cooperation Working Group | British Library Conference Proceedings | 1996


    Transforming Maritime Safety: Data-driven Applications for the Real-Time Detection and Mitigation of Maritime Incidents

    Grigoropoulos, Georgios / Kapeliaris, Alexandros Troupiotis - / Chamatidis, Ilias et al. | DataCite | 2025


    Motor Vehicles Forecasting in Kolhapur City Using Combined Grey Model

    Shinde, Sagar Maruti / Karjinni, Vilas Vijay | Springer Verlag | 2023