Ensemble learning for energy performance prediction of residential buildings

Keyphrases

• Residential Buildings 100%
• Energy Performance Prediction 100%
• Ensemble Learning 100%
• Machine Learning Classification 66%
• Support Vector Machine 66%
• Building Energy Performance 66%
• Classification Basis 33%
• Learning Classification 33%
• Artificial Neural Network 33%
• Rating Scales 33%
• Computational Efficiency 33%
• Extra Trees 33%
• United Kingdom 33%
• Energy Consumption Prediction 33%
• K-nearest Neighbor (K-NN) 33%
• Climate Change 33%
• Parameter Optimization 33%
• Human Existence 33%
• Nearest Neighbor Tree 33%
• Performance Features 33%
• Gradient Boosting Decision Tree 33%
• Thermal Pollution 33%
• Energy Performance Certificates 33%
• Decision Tree 33%
• Building Energy Efficiency 33%
• Energy in Buildings 33%
• Air Pollution 33%
• Accurate Model 33%
• Machine Learning Techniques 33%
• Energy Demand 33%
• Energy Consumed 33%
• Regression Model 33%
• Environmental Issues 33%
• Urbanization 33%
• Random Forest 33%
• Optimization Efficiency 33%
• Energy Performance of Residential Buildings 33%

Engineering

• Residential Building 100%
• Performance Prediction 100%
• Energy Performance 100%
• Energy Engineering 75%
• Learning System 50%
• Support Vector Machine 50%
• Building Energy Efficiency 25%
• Nearest Neighbor 25%
• Random Forest 25%
• Machine Learning Technique 25%
• Climatic Change 25%
• Good Result 25%
• Building Energy Performance 25%
• Artificial Neural Network 25%
• Air Pollution 25%
• Past Decade 25%
• Computational Efficiency 25%
• United Kingdom 25%
• Thermal Pollution 25%
• Climate Change 25%