In Vessel Traffic Service (VTS), prediction of ship traffic flow is essential for VTS operator. But, by external force such as tidal current, wind, wave and other regulations, it was difficult to predict ship traffic flow. In this paper, in order to utilize ship trajectory big data by Automatic Identification System (AIS), we propose the method to convert ship speed data to categorical data dividing ship navigating routes into several gate lines. Then experiments to verify model accuracy conduct using multiple input and output variables with artificial neural network.


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    Titel :

    Preprocessing Ship Trajectory Data for Applying Artificial Neural Network in Harbour Area


    Beteiligte:
    Kim, Kwang Il (Autor:in) / Lee, Keon Myung (Autor:in)


    Erscheinungsdatum :

    01.11.2017


    Format / Umfang :

    300112 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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