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《Journal of Electric Power Science and Technology》 2015-01
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Research on electricity consumption prediction with the algebraic polynomial model

SHENG Li-zeng;ZENG Zhe-zhao;LI Sha;School of Electrical and Information Engineering,Changsha University of Science and Technology;  
Aiming at the power grid layout and construction requirements,future electricity consumption can be reasonable predicted according to the historical data. Thus,the polynomial prediction model was set up with the recursive least squares algorithm,and the algebraic polynomial prediction method was proposed in this paper. With polynomial fitting model,the method constructs neural network topology structure,and the structure parameters can be used as the weights of neural network. Using the recursive least squares method for training the weights of neural network,the method obtained polynomial model parameters. The simulation results showed that,this method has good fitting results and good prediction function,which has great application value in power consumption forecast.
【Fund】: 湖南省自然科学基金(11JJ6064);; 湖南省科技计划项目(2011GK3122);; 长沙理工大学开放基金(13kfjj07)
【CateGory Index】: TP18;TM73
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