In order to improve port Vessel Traffic Services (VTS) centers intelligence to realize intelligent monitoring and warning ships in the port. Used ship's position of time $\mathrm{t}_{\mathrm{k}-3}, \mathrm{t}_{\mathrm{k}-2},\mathrm{t}_{\mathrm{k}-1}$ and the time interval between $\mathrm{t}_{\mathrm{k}}$ and $\mathrm{t}_{\mathrm{k}-1}$ as input vector, the ship's position of time $\mathrm{t}_{\mathrm{k}}$ as output vector. Built a BP neural network based on irregular time series. Select the Automatic Identification System (AIS) data which a ship navigated in the port of Tianjin within three months to train the network, select a voyage data of the ship sailing in the port to test the network. Test results showed that the model has a high accuracy to forecast the track of ship in the port.


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    Titel :

    Forecast Position for Ship in Port Based on Irregular Time Series


    Beteiligte:
    Tang, Huang (Autor:in) / Yin, Yong (Autor:in)


    Erscheinungsdatum :

    01.02.2022


    Format / Umfang :

    3059950 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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