A review of physics-informed machine learning for building energy modeling

Keyphrases

• Building Energy Simulation 100%
• Physics-informed Machine Learning 100%
• Physics-informed 30%
• Machine Learning Techniques 20%
• Modelling Practice 20%
• Building Renovation 20%
• Effective Integration 10%
• Computational Modeling 10%
• Machine Learning Algorithms 10%
• Data-driven Approach 10%
• Training Data 10%
• Physics-based 10%
• Sustainable Design 10%
• Architectural Design 10%
• Ensemble Model 10%
• Algorithm Development 10%
• Sustainable Building 10%
• Building Energy Consumption 10%
• Deep Learning Algorithm 10%
• Training Quality 10%
• Data-driven Modeling 10%
• Machine Learning Models 10%
• Edge Machine Learning 10%
• Building Development 10%
• Design Building 10%
• Deep Machine Learning 10%
• Machine Learning Learning 10%
• Building Resilience 10%
• Resilience Analysis 10%
• Physics Principles 10%
• Modeling Approaches 10%
• Novel Modeling 10%
• Physical Information 10%
• Widespread Adoption 10%
• Smart Building Control 10%
• Physics Data 10%
• Potential Directions 10%
• Prior Physical Knowledge 10%

Engineering

• Energy Modeling 100%
• Physics-Informed Machine Learning 100%
• Machine Learning Method 20%
• Architectural Design 20%
• Learning System 20%
• Interpretability 20%
• Cutting Edge 10%
• Optical Spectrum 10%
• Generality 10%
• Research Work 10%
• Machine Learning Algorithm 10%
• Sustainable Building 10%
• Intelligent Buildings 10%
• Loss Function 10%
• Computer Simulation 10%
• Deep Learning Method 10%
• Building Retrofitting 10%
• Critical Component 10%