An annual load forecasting model based on support vector regression with differential evolution algorithm

Applied Energy

Volumn 94, Issue , 2012, Pages 65-70

  Wang, Jianjun ^a   Li, Li ^b   Niu, Dongxiao ^a   Tan, Zhongfu ^a  

^a NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

^b BEIJING INFORMATION SCIENCE AND TECHNOLOGY UNIVERSITY   (China)

Author keywords

Annual load forecasting; Differential evolution (DE); Support vector regression (SVR)

Indexed keywords

COMPUTER SIMULATION; ELECTRIC INDUSTRY; EVOLUTIONARY ALGORITHMS; FORECASTING; NEURAL NETWORKS; REGRESSION ANALYSIS; VECTORS;

ANNUAL LOAD CURVE; BACK PROPAGATION ARTIFICIAL NEURAL NETWORK (BPANN); DE ALGORITHMS; DEFAULT PARAMETERS; DIFFERENTIAL EVOLUTION (DE); DIFFERENTIAL EVOLUTION ALGORITHMS; ELECTRIC POWER INDUSTRIES; FORECASTING PROBLEMS; KEYPOINTS; LOAD FORECASTING; LOAD FORECASTING MODEL; NONLINEAR CHARACTERISTICS; NONLINEAR PROBLEMS; REGRESSION FORECASTING MODEL; SUPPORT VECTOR REGRESSION (SVR);

ELECTRIC LOAD FORECASTING;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; ELECTRICAL POWER; FORECASTING METHOD; NUMERICAL MODEL; REGRESSION ANALYSIS;

EID: 84862777006     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2012.01.010     Document Type: Review

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