Noise model based ν-support vector regression with its application to short-term wind speed forecasting

Neural Networks

Volumn 57, Issue , 2014, Pages 1-11

  Hu, Qinghua ^a,b   Zhang, Shiguang ^a,c   Xie, Zongxia ^b   Mi, Jusheng ^a,d   Wan, Jie ^e  

^a HEBEI NORMAL UNIVERSITY   (China)

^b TIANJIN UNIVERSITY   (China)

^c HENGSHUI UNIVERSITY   (China)

^d Key Lab of Computational Mathematics and Applications   (China)

^e HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Inequality constraints; Loss function; Noise model; Support vector regression; Wind speed forecasting

Indexed keywords

BAYESIAN NETWORKS; CONSTRAINT THEORY; FORECASTING; GAUSSIAN NOISE (ELECTRONIC); LAGRANGE MULTIPLIERS; VECTORS; WIND; WIND POWER;

AUGMENTED LAGRANGE MULTIPLIER METHODS; INEQUALITY CONSTRAINT; LOSS FUNCTIONS; NOISE MODELING; SHORT-TERM WIND SPEED FORECASTING; SHORT-TERM WIND SPEED PREDICTIONS; SUPPORT VECTOR REGRESSION (SVR); WIND SPEED FORECASTING;

SUPPORT VECTOR REGRESSION;

ANALYTIC METHOD; ANALYTICAL ERROR; ARTICLE; AUGMENTED LAGRANGE MULTIPLIER METHOD; BAYES THEOREM; FORECASTING; LINEAR SYSTEM; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; NOISE MODEL; NONLINEAR SYSTEM; PREDICTION; PRIORITY JOURNAL; STATISTICAL MODEL; SUPPORT VECTOR MACHINE; WIND POWER; METEOROLOGY; NORMAL DISTRIBUTION; PROCEDURES; REGRESSION ANALYSIS; THEORETICAL MODEL; WIND;

BAYES THEOREM; METEOROLOGY; MODELS, THEORETICAL; NORMAL DISTRIBUTION; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; WIND;

EID: 84901427227     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2014.05.003     Document Type: Article

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