A prediction method is proposed based on RBF neural network through in-depth study of power load of ships. Before predicting the ship's power load, it is necessary to pre-process various data of the ship, screen and clean the abnormal data, and then normalise the normal samples, and finally construct a model to process the data and optimise the model according to the results. Various data of an electric propulsion ship are selected as the input reference of the model, and a prediction model is established using Matlab. The design method is shown to be one of the methods with high prediction accuracy according to the experimental results, and shows high model credibility in prediction.


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    Titel :

    Load Forecasting for Electric Propulsion Vessels Based on RBF Neural Network


    Beteiligte:
    Li, Puze (Autor:in) / Qiu, Chengjun (Autor:in) / Qu, Wei (Autor:in) / Li, Ke (Autor:in) / Liu, Haozheng (Autor:in) / Tao, Wei (Autor:in)


    Erscheinungsdatum :

    28.09.2024


    Format / Umfang :

    966742 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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