The number of ships has increased in recent years and the requirements for maritime security protection have become more stringent. It is important to improve the prediction accuracy and efficiency of maritime target in order to sustain maritime security. According to the real-time, efficiency and accuracy requirements of maritime target trajectory prediction, a prediction model based on RNN network is proposed to realize maritime target trajectory prediction based on AIS data. This paper uses AIS data between Longkou and Dalian to conduct experiments, and compares the prediction effects of two network models RNN and LSTM on the maritime target trajectory. It proves that the RNN network model has higher prediction accuracy and stronger learning ability. Based on the experimental results, this paper analyzes the characteristics of deep learning in long-term prediction and historical data dependence at the same time.


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    Titel :

    Maritime Target Trajectory Prediction Model Based on the RNN Network


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Liang, Qilian (Herausgeber:in) / Wang, Wei (Herausgeber:in) / Mu, Jiasong (Herausgeber:in) / Liu, Xin (Herausgeber:in) / Na, Zhenyu (Herausgeber:in) / Chen, Bingcai (Herausgeber:in) / Jin, Jialong (Autor:in) / Zhou, Wei (Autor:in) / Jiang, Baichen (Autor:in)


    Erscheinungsdatum :

    2020-02-01


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch