Prediction of daily energy consumption for ship special coating maintenance based on stochastic forest regression
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).
energy consumption predictionrandom forest regressionLOF algorithmship special coating
国家科技期刊平台
NSTL
万方数据
维普
