A study of the importance of occupancy to building cooling load in prediction by intelligent approach

Energy Conversion and Management

Volumn 52, Issue 7, 2011, Pages 2555-2564

  Kwok, Simon S K ^a   Lee, Eric W M ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Artificial neural network; Building occupancy; Cooling load

Indexed keywords

COOLING; ENERGY CONSERVATION; FORECASTING; INVERSE PROBLEMS; NEURAL NETWORKS; OFFICE BUILDINGS;

ARTIFICIAL NEURAL NETWORK MODELS; BUILDING COOLING LOAD; BUILDING OCCUPANCY; COMPUTATIONAL MODEL; COOLING LOAD; ENERGY-SAVING MEASURES; HONG KONG OBSERVATORIES; PROBABILISTIC ENTROPY;

AIR CONDITIONING;

EID: 79952783600     PISSN: 01968904     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enconman.2011.02.002     Document Type: Article

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