New parallel support vector regression for predicting building energy consumption

IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MCDM 2011: 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making

Volumn , Issue , 2011, Pages 14-21

  Zhao, Hai Xiang ^a   Magoules, Frédéric ^a  

^a ECOLE CENTRALE PARIS   (France)

Author keywords

Building energy consumption; Map Reduce; Multi core; Parallel computing; Support Vector Regression (SVR)

Indexed keywords

BUILDING ENERGY CONSUMPTION; DATA SETS; DECOMPOSITION METHODS; GRADIENT VECTORS; MAP-REDUCE; MODEL TRAINING; MULTI CORE; MULTI PROCESSOR SYSTEMS; PARALLEL IMPLEMENTATIONS; PARALLELIZATIONS; SEQUENTIAL MINIMAL OPTIMIZATION; SHARED MEMORIES; SPEED INCREASE; STORAGE REQUIREMENTS; SUPPORT VECTOR REGRESSION (SVR); SUPPORT VECTOR REGRESSIONS;

ARTIFICIAL INTELLIGENCE; DECISION MAKING; ENERGY UTILIZATION; PARALLEL ARCHITECTURES; REGRESSION ANALYSIS; VECTORS;

ELECTRIC LOAD FORECASTING;

EID: 79961153435     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SMDCM.2011.5949289     Document Type: Conference Paper

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