Space cooling energy usage prediction based on utility data for residential buildings using machine learning methods

Keyphrases

• Machine Learning Techniques 100%
• Prediction Method 100%
• R2 Value 100%
• Residential Buildings 100%
• Energy Consumption Prediction 100%
• Cooling Energy 100%
• Space Cooling 100%
• Utility Data 100%
• Energy Performance 50%
• Performance Prediction 50%
• Optimal Performance 50%
• Model Prediction 50%
• Performance Level 50%
• Regression Techniques 50%
• Feature Analysis 50%
• Building Performance 50%
• Energy Use 50%
• Weather Data 50%
• Infrastructure-free 50%
• Homeowners 50%
• Building Characteristics 50%
• Climate Zones 50%
• Anonymized 50%
• Cross-validation Method 50%
• Weather Characteristics 50%
• Energy Applications 50%
• Cooling Energy Consumption 50%
• Household Energy 50%
• K-fold Cross-validation 50%
• Extreme Gradient Boosting(XGBoost) 50%
• Hyperparameter Optimization 50%
• Modeling Procedure 50%
• Accurate Prediction Model 50%

Engineering

• Energy Usage 100%
• Residential Building 100%
• Space Cooling 100%
• Machine Learning Method 100%
• Energy Performance 50%
• Optimal Performance 50%
• Model Prediction 50%
• Regression Technique 50%
• Accurate Prediction 50%
• Prediction Performance 50%
• Climate Zone 50%
• Input Information 50%
• Building Performance 50%
• Interpretability 50%
• Xgboost 50%
• United States of America 50%