N.-L. Tai, H.-Q. Zhai, J. Ye, and L.-B. Qi
[1] T. Senjyu, P. Mandal, & K. Uezato, Next day load curveforecasting using hybrid correction method, IEEE Transactionson Power Systems, 20(1), 2005, 102–109. [2] S. Rahman & O. Hazim, A generalized knowledge-based ap-proach to short-term load forecasting, IEEE Transactions onPower Systems,. 8(2), 1993, 508–515. [3] H.S. Hippert, C.E. Pedreira, & R.C. Souza, Neural networkfor short-term load forecasting: A review and evolution, IEEETransactions on Power Systems, 16(1), 2001, 44–55. [4] G.C. Liao & T.P. Tsao, Application of a fuzzy neural networkcombined with a chaos genetic algorithm and simulated an-nealing to short-term load forecasting, IEEE Transactions onPower Systems, 10(3), (2006), 330–340. [5] B.J. Chen, M.W. Chang, & C.J. Lin, Load forecasting usingsupport vector machines: A study on EUNITE competition2001, IEEE Transactions on Power Systems, 19(4), 2004,1821–1830. [6] N. Amjady, Short-term hourly load forecasting using time-series modeling with peak load estimation capability, IEEETransactions on Power Systems, 16(4), 2001, 798–805. [7] J. Taylor & R. Buizza, Neural network load forecasting withweather ensemble predictions, IEEE Transactions on PowerSystems, 17(3), 2002, 626–632. [8] Z.B.-Qing, C.H.-Zhong, L.Q.-Shan, et al. Short-term loadforecasting based on attribute reduction algorithm of roughsets and support vector machine, Power System Technology,30(5), 2006, 56–60. [9] H.T. Yang, C.M. Huang, A new short-term load forecastingapproach using self-organizing fuzzy ARMAX models, IEEETransactions Power Systems, 18(2), 2003, 673–679. [10] C.Q. Kang, X. Cheng, Q. Xia, Y.H. Huang, & F. Gao, Novelapproach considering load-relative factors in short-term loadforecasting, Electric Power Systems Research, 70(2), 2004,99–107. [11] C.-L. Hor, S.J. Watson & S. Majithia, Analyzing the impactof weather variables on monthly electricity demand, IEEETransactions on Power Systems, 20(4), 2005, 2078–2085.
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