Application of Least Squares Support Vector Machine(LS-SVM) Based on Time Series in Power System Monthly Load Forecasting

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[1]  Johan A. K. Suykens,et al.  Weighted least squares support vector machines: robustness and sparse approximation , 2002, Neurocomputing.

[2]  Ming-Wei Chang,et al.  Load forecasting using support vector Machines: a study on EUNITE competition 2001 , 2004, IEEE Transactions on Power Systems.

[3]  Yongli Wang,et al.  Support vector machines based on Lyapunov exponents in power load forecasting model , 2008, APCCAS 2008 - 2008 IEEE Asia Pacific Conference on Circuits and Systems.

[4]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[5]  Ming-Wei Chang,et al.  Load Forecasting Using Support Vector Machines: A Study on EUNITE Competition 2001 , 2004, IEEE Transactions on Power Systems.

[6]  Shi Peng-fei,et al.  Applications of optimization combination model for medium-long term load forecasting , 2010, 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems.

[7]  Ye Zhang,et al.  Short-Term Load Forecasting Model Based on LS-SVM in Bayesian Inference , 2009, 2009 First International Workshop on Education Technology and Computer Science.

[8]  Yin He-jun APPLICATION OF SUPPORT VECTOR MACHINES BASED ON TIME SEQUENCE IN POWER SYSTEM LOAD FORECASTING , 2004 .

[9]  S. Fan,et al.  Short-term load forecasting based on an adaptive hybrid method , 2006, IEEE Transactions on Power Systems.

[10]  Mihai Gavrilas,et al.  Medium-term load forecasting with artificial neural network models , 2001 .