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Hybrid approach for energy consumption prediction: Coupling data-driven and physical approaches
Kadir Amasyali,
Nora El-Gohary
Civil and Environmental Engineering
National Center for Supercomputing Applications (NCSA)
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Dive into the research topics of 'Hybrid approach for energy consumption prediction: Coupling data-driven and physical approaches'. Together they form a unique fingerprint.
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Keyphrases
Hybrid Method
100%
Data-driven Approach
100%
Physical Approach
100%
Energy Consumption Prediction
100%
Machine Learning Models
50%
Generated Data
50%
Cooling Energy Consumption
50%
Occupant Behavior
50%
Modeling Approach
25%
Weather Conditions
25%
Unseen
25%
Hybrid Model
25%
Machine Learning Approach
25%
Performance Prediction
25%
Office Building
25%
Pennsylvania
25%
Improved Prediction
25%
Physical Modeling
25%
Ensemble Model
25%
Consumption-based
25%
EnergyPlus
25%
Intended Use
25%
Building Energy Prediction
25%
Hybrid Machine Learning
25%
Engineering
Energy Engineering
100%
Hybrid Approach
100%
Limitations
50%
Real Data
50%
Occupant Behavior
50%
Hybrid Model
25%
Physical Modeling
25%
EnergyPlus
25%
Office Buildings
25%
Energy Building
25%
Prediction Performance
25%
Learning Approach
25%
Reference Building
25%
Material Science
Mechanical Strength
100%