Application of SVR with chaotic GASA algorithm in cyclic electric load forecasting

Energy

Volumn 45, Issue 1, 2012, Pages 850-858

  Zhang, Wen Yu ^a   Hong, Wei Chiang ^b   Dong, Yucheng ^c   Tsai, Gary ^d   Sung, Jing Tian ^d   Fan, Guo feng ^e  

^a ZHEJIANG UNIVERSITY OF FINANCE AND ECONOMICS   (China)

^b ORIENTAL INSTITUTE OF TECHNOLOGY   (Taiwan)

^c Department of Management Science and System Science   (China)

^d INSTITUTE FOR INFORMATION INDUSTRY   (Taiwan)

^e KUNMING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Chaotic genetic algorithm simulated annealing (CGASA); Electric load forecasting; Seasonal mechanism; Support vector regression (SVR)

Indexed keywords

ALGORITHMS; ECONOMICS; FORECASTING; SIMULATED ANNEALING;

ACCURATE PERFORMANCE; ANNEALING ALGORITHM; CHAOTIC GENETIC ALGORITHM-SIMULATED ANNEALING (CGASA); CHAOTIC ITERATION; CHAOTIC SEQUENCE; CYCLIC CHANGES; ECONOMIC ACTIVITIES; FORECASTING ACCURACY; FORECASTING PERFORMANCE; HYBRID ALGORITHMS; LOAD FORECASTING; LOCAL OPTIMA; MODEL YIELDS; NUMERICAL EXAMPLE; SUPPORT VECTOR REGRESSION (SVR);

ELECTRIC LOAD FORECASTING;

ALGORITHM; CYCLIC LOADING; DEMAND ANALYSIS; ELECTRICAL PROPERTY; FORECASTING METHOD; NUMERICAL MODEL; REGRESSION ANALYSIS;

EID: 84865413861     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2012.07.006     Document Type: Article

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