Research on Accurate Prediction of Operating Energy Consumption of Green Buildings Based on Improved Machine Learning

Abstract

Aiming at the problem that the current prediction model constructed by the current accurate prediction method of green building operation energy consumption is relatively backward, resulting in large errors in the prediction results, an accurate prediction method of green building operation energy consumption based on improved machine learning is designed. Box plots and data-driven systems were used to complete data collection and preprocessing of energy consumption for green building operations. The gray correlation function is used to analyze the parameters of building energy consumption. Improve machine learning algorithms and build energy consumption prediction models. To date, the design of an accurate prediction of green building operation energy consumption based on improved machine learning has been completed. Experiments have confirmed that the method in this paper can accurately predict the energy consumption of green buildings and improve the efficiency of prediction.