Forecasting Electricity Market Price Spikes Based on Bayesian Expert with Support Vector Machines
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Wei Wu | Li Mo | Jianzhong Zhou | Chengjun Zhu | Jian-zhong Zhou | Wei Wu | L. Mo | C. Zhu | Chengjun Zhu
[1] A. Venturini,et al. Day-ahead market price volatility analysis in deregulated electricity markets , 2002, IEEE Power Engineering Society Summer Meeting,.
[2] P. Luh,et al. Forecasting power market clearing price and its discrete PDF using a Bayesian-based classification method , 2001, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).
[3] Z. Dong,et al. Electricity market price spike forecast with data mining techniques , 2005 .
[4] A.J. Conejo,et al. Day-ahead electricity price forecasting using the wavelet transform and ARIMA models , 2005, IEEE Transactions on Power Systems.
[5] B. Ramsay,et al. A neural network based estimator for electricity spot-pricing with particular reference to weekend and public holidays , 1998, Neurocomputing.
[6] Junhua Zhao,et al. A general method for electricity market price spike analysis , 2005, IEEE Power Engineering Society General Meeting, 2005.
[7] A no-arbitrage equilibrium model for the regional electricity market of China , 2005, 2005 IEEE International Conference on Industrial Technology.
[8] Johan A. K. Suykens,et al. Financial time series prediction using least squares support vector machines within the evidence framework , 2001, IEEE Trans. Neural Networks.
[9] J. Contreras,et al. ARIMA models to predict next-day electricity prices , 2002 .
[10] Lijuan Cao,et al. Support vector machines experts for time series forecasting , 2003, Neurocomputing.