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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    Title :

    Forecast Position for Ship in Port Based on Irregular Time Series


    Contributors:
    Tang, Huang (author) / Yin, Yong (author)


    Publication date :

    2022-02-01


    Size :

    3059950 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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