Wind speed forecasting model study based on Support Vector Machine

Taiyangneng Xuebao/Acta Energiae Solaris Sinica

Volumn 31, Issue 7, 2010, Pages 928-932

  Zhang, Hua ^a   Zeng, Jie ^a  

^a NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

Author keywords

Short term predict; Support vector machine (SVM); Wind speed forecasting

Indexed keywords

MEAN ABSOLUTE PERCENTAGE ERROR; SHORT TERM; SHORT-TERM WIND SPEED FORECASTING; SUPPORT VECTOR MACHINE (SVM); SVM MODEL; WIND DATA; WIND SPEED; WIND SPEED FORECASTING;

SPEED; SUPPORT VECTOR MACHINES; VECTORS; WIND EFFECTS;

FORECASTING;

EID: 77957950260     PISSN: 02540096     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (13)

1. 2005, 6(12): 21-24.
2. Bossanyi E A. Short-term wind prediction using Kalman filters[J]. Wind Engineering, 1985, 9(1): 1-7.
3. Alexiadis M, Dokopoulos P, Sahsamanoglou H, et al. Short term forecasting of wind speed and related electrical power[J]. Solar Energy, 1998, 63(1): 61-68.
4. Kariniotakis G, Stavrakakis G, Nogaret E. Wind power forecasting using advanced neural network models[J]. IEEE Trans Energy Conversion, 1996, 11(4): 762-767.
5. Cortes C, Vapnik V. Support vector networks[J]. Machine Learning, 1995, 20(3): 273-297.
6. 2006, 27(4): 321-325.
7. Müller K R, Smola A J, Ratsch G, et al. Predicting time series with support vector machines. In: Proc. of ICANN [J]. Springer Lecture Notes in Computer Science, 1997, 999-1005.
8. Cui Weidong, Zhou Zhihua, Li Xing. Research of support vector machines[J]. Computer Engineering and Applications, 2001, 1: 58-61.
9. Vapnik V. The Nature of statistical learning theory[M]. New York: Springer-Verlag, 1995.
10. 2006, 27(3): 223-227.
11. 2008, 20(1): 85-86.
12. 2006, 7(4): 231-232.
13. Qu Wenglong, Fan Guangquan, Yang Bingru. Research on complicated time series prediction based on support vector machines[J]. Computer Engineering, 2005, 23(12): 1-2.