DocumentCode
2289700
Title
Medium and long-term electric load forecasting based on chaos SVM
Author
Wang Deji ; Lian Jie ; Xu Bo ; Ma Yumin ; Zhang Yanbo
Author_Institution
Staff Dev. Inst., China Nat. Tobacco Corp., Zhengzhou, China
fYear
2012
fDate
6-8 July 2012
Firstpage
660
Lastpage
663
Abstract
Because traditional prediction algorithm can not accurately forecast long-term electricity load, chaos SVM prediction algorithm was introduced and some of its characteristics were discussed. The kernel function was chosen under the guidance of the geometric information. The experiment shows that the algorithm is more accurate and effective than the others.
Keywords
load forecasting; power engineering computing; support vector machines; chaos SVM prediction algorithm; geometric information; kernel function; long-term electric load forecasting; long-term electricity load; medium-term electric load forecasting; Automation; Chaos; Electronic mail; Load forecasting; Pipelines; Prediction algorithms; Support vector machines; Chaos; Prediction; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location
Beijing
Print_ISBN
978-1-4673-1397-1
Type
conf
DOI
10.1109/WCICA.2012.6357961
Filename
6357961
Link To Document