Potential of artificial neural networks to predict thermal sensation votes

Applied Energy

Volumn 161, Issue , 2016, Pages 412-424

  von Grabe, Jörn ^a  

^a UNIVERSITY OF LIECHTENSTEIN   (Liechtenstein)

Author keywords

Artificial neural network; Occupant behavior; Predicted mean vote; Prediction; Thermal sensation

Indexed keywords

BUILDINGS; ENERGY CONSERVATION; ENERGY UTILIZATION; NEURAL NETWORKS; SENSORY PERCEPTION; THERMAL COMFORT;

ADAPTIVE MODELING; BUILDING SIMULATION; OCCUPANT BEHAVIOR; PREDICTED MEAN VOTE; PREDICTION QUALITY; THERMAL ENVIRONMENT; THERMAL SENSATION VOTES; THERMAL SENSATIONS;

FORECASTING;

ADAPTIVE MANAGEMENT; ARCHITECTURAL DESIGN; ARTIFICIAL NEURAL NETWORK; CONCEPTUAL FRAMEWORK; ENERGY CONSERVATION; FUEL CONSUMPTION; OPTIMIZATION; THERMAL REGIME;

PAPAYA MOSAIC VIRUS;

EID: 84944706430     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2015.10.061     Document Type: Article

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