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

Annual load forecasting is very important for the electric power industry. As influenced by various factors, an annual load curve shows a non-linear characteristic, which demonstrates that the annual load forecasting is a non-linear problem. Support vector regression (SVR) is proven to be useful in...

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Veröffentlicht in:	Applied energy Jg. 94; S. 65 - 70
Hauptverfasser:	Wang, Jianjun, Li, Li, Niu, Dongxiao, Tan, Zhongfu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Kidlington Elsevier Ltd 01.06.2012 Elsevier
Schlagworte:	algorithms Annual load forecasting Applied sciences Differential evolution (DE) electric power Energy Exact sciences and technology industry neural networks Support vector regression (SVR) Annual load forecasting Support vector regression (SVR) Differential evolution (DE)
ISSN:	0306-2619, 1872-9118
Online-Zugang:	Volltext
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