Predicting energy consumption is an important task in the intelligent energy efficiency optimization of ship maintenance, with special coating (spec coat) being the core aspect.In this experiment, the random forest regression (RFR) model was employed to analyze the daily energy consumption of ship maintenance for special coating.The dataset was preprocessed by removing outliers, randomizing and standardizing the data.Subsequently, the RFR model was trained and fitted using historical data of daily energy consumption in ship maintenance.The RFR model was optimized using grid search with cross-validation, and analysis of daily energy consumption data for ship special coating maintenance using optimized RFR model.Comparative experiments were conducted with other models.The results revealed that the optimized RFR model outperformed several other models, achieving an R-squared value of 93.25% and significantly lower mean squared error (MSE).


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Prediction of daily energy consumption for ship special coating maintenance based on stochastic forest regression


    Beteiligte:
    Ruiping GAN (Autor:in) / Xinmin REN (Autor:in) / Jun JIANG (Autor:in) / Peng LI (Autor:in) / Xiaobing ZHOU (Autor:in)


    Erscheinungsdatum :

    2024



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Ship oil consumption prediction method based on elastic regression network

    ZUO YI / LI SHANSHAN / LI XINYU et al. | Europäisches Patentamt | 2023

    Freier Zugriff

    Ship energy consumption prediction method based on data driving

    WANG LIPENG / ZHANG ZHI / ZHU QIDAN et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    Ship fuel consumption prediction method based on distributed energy efficiency calculation

    YI MINGJING / YI XIAOBING / HE LIMING et al. | Europäisches Patentamt | 2024

    Freier Zugriff


    Oil consumption prediction method for intelligent ship

    WEI DAOXIN / WANG YANG / ZHANG ZHENG et al. | Europäisches Patentamt | 2024

    Freier Zugriff