Analysis of daily solar power prediction with data-driven approaches

Applied Energy

Volumn 126, Issue , 2014, Pages 29-37

  Long, Huan ^a   Zhang, Zijun ^a   Su, Yan ^b  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^b UNIVERSITY OF MACAU   (Macao)

Author keywords

Artificial neural network (ANN); Data mining; Solar power prediction; Support vector machine (SVM); Time series model

Indexed keywords

DATA MINING; FORECASTING; NEAREST NEIGHBOR SEARCH; NEURAL NETWORKS; SOLAR ENERGY; SUPPORT VECTOR MACHINES; SUPPORT VECTOR REGRESSION;

COMPUTATIONAL RESULTS; DATA-DRIVEN ALGORITHM; K NEAREST NEIGHBOR (KNN); METEOROLOGICAL PARAMETERS; MULTI-STEP-AHEAD PREDICTIONS; MULTIVARIATE LINEAR REGRESSIONS; POWER PREDICTIONS; TIME SERIES MODELING;

PREDICTIVE ANALYTICS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; DATA MINING; NUMERICAL MODEL; PREDICTION; REGRESSION ANALYSIS; RENEWABLE RESOURCE; SOLAR POWER;

EID: 84899128304     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2014.03.084     Document Type: Article

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