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《Electric Power Automation Equipment》 2003-03
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Combined power load forecast model based on Matlab neural network toolbox

LIU Shuang,YANG Li-xi,WANG Zhi-gang,JIA De-feng,CHEN Gen-yong(College of Electrical Engineering,Zhengzhou University,Zhengzhou450002,China)  
Combined forecast is an effective method in power load forecast,which usually adopts weighted processing of each forecast model and requires stable model error in combined forecast.But the forecast errors are not well proportioned in power load forecast.An artificial neural network based combined forecast model is presented,which automatically adjusts the weight of each forecast model by network training for complicated non-linear system.The Matlab artificial neural network toolbox is used to avoid the complicated model structure and long training time in establishing the combined forecast model.The model is not only simpler in programming,but also quicker in convergence.The calculation example shows that it is practical and effective.
【CateGory Index】: TM714.1
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