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
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;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
DOI :
10.1109/WCICA.2012.6357961
