A large-scale study on predicting and contextualizing building energy usage

Proceedings of the National Conference on Artificial Intelligence

Volumn 2, Issue , 2011, Pages 1349-1356

  Kolter, J Zico ^a   Ferreira Jr , Joseph ^b  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BEHAVIOR CHANGE; BUILDING ENERGY; CAMBRIDGE; COMMERCIAL BUILDING; CONTEXTUALIZE; DATA SETS; DATA-DRIVEN APPROACH; END USERS; ENERGY USAGE; LEARNING METHODS; NON-PARAMETRIC; PRICING SCHEME;

ARTIFICIAL INTELLIGENCE; BEHAVIORAL RESEARCH; ELECTRIC LOAD FORECASTING; ENERGY UTILIZATION; OFFICE BUILDINGS; PHASE INTERFACES; RETROFITTING;

ENERGY CONSERVATION;

EID: 80055058091     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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