Machine learning baseline energy model (mlbem) to evaluate prediction performances in building energy consumption

HIGHLIGHTS

• What: The hyperparameters of each model were tweaked to achieve the greatest possible performance of BEM, and the models were initially evaluated to estimate the performance of the MLBEM model in the step ahead of 12 hours. In this study, the performance is assessed through residual error metrics, namely Root Mean Square Error (RMSE), Mean Square Error (MSE), and Mean Absolute Error (MAE). The tuning process for the ARIMAX model focuses on AutoRegressive Lags (ARlags), D (order of differencing), and Moving Average Lags (MALags).
• Who: gerry from the (UNIVERSITY) have published the research: Machine Learning . . .
  

   

  

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