Although a huge amount of information is available in all kinds of marine safety databases, only a small part can be used directly. The disorganized information from different sources leads to a mixture of format and definition. In the work reported in this paper, the Dempster–Shafer theory (DST) of evidence was applied to combine evidence (i.e., a piece of information that supports a claim) from different sources. The method is regarded as a generalization of the Bayesian theory and can avoid two difficulties in classical probability theory: handling the conflicting information and assigning prior probabilities. The work of data fusion was demonstrated first by a decision fusion problem that involved the reconciliation of contradictory expert reports. The DST can provide a decision maker with a comprehensive result through the combination of different experts’ opinions. Second, fusion was conducted of two representative maritime incident databases: that of the Global Integrated Shipping Information System and that of the International Chamber of Commerce. Although the records in the databases had some defects (e.g., disorder, error, contradiction), the DST was able to work effectively and calculate an uncertainty interval of incident.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Data Fusion of Maritime Incident Databases with Dempster–Shafer Theory


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Li, Yi-Zhou (author) / Hu, Hao (author) / Huang, Dao-Zheng (author)


    Publication date :

    2014-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    A Dempster-Shafer Sensor Fusion Approach for Traffic Incident Detection and Localization

    Mehrannia, Pouya / Moghadam, Aida Arman / Basir, Otman A. | IEEE | 2018


    Fault-tolerant interval estimation fusion by Dempster-Shafer theory

    Baohua Li, / Yunmin Zhu, / Rong Li, X. | IEEE | 2002


    S14 Fault-Tolerant Interval Estimation Fusion By Dempster-Shafer Theory

    Li, B. / Zhu, Y. / Li, X. R. et al. | British Library Conference Proceedings | 2002