A hybrid annual power load forecasting model based on generalized regression neural network with fruit fly optimization algorithm

A hybrid annual power load forecasting model based on generalized regression neural network with fruit fly optimization algorithm

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時間：2019-07-14

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1、Knowledge-BasedSystems37(2013)378–387ContentslistsavailableatSciVerseScienceDirectKnowledge-BasedSystemsjournalhomepage:www.elsevier.com/locate/knosysAhybridannualpowerloadforecastingmodelbasedongeneralizedregressionneuralnetworkwithfruit?yoptimizationalgorithmHong-zeLi,SenGuo?,Chun-ji

2、eLi,Jing-qiSunSchoolofEconomicsandManagement,NorthChinaElectricPowerUniversity,Beijing102206,ChinaarticleinfoabstractArticlehistory:AccurateannualpowerloadforecastingcanprovidereliableguidanceforpowergridoperationandpowerReceived4April2012constructionplanning,whichisalsoimportantforthe

3、sustainabledevelopmentofelectricpowerindus-Receivedinrevisedform30May2012try.Theannualpowerloadforecastingisanon-linearproblembecausetheloadcurveshowsanon-linearAccepted18August2012characteristic.Generalizedregressionneuralnetwork(GRNN)hasbeenproventobeeffectiveindealingAvailableonline

4、30August2012withthenon-linearproblems,butitisveryregretfully?ndsthattheGRNNhaverarelybeenappliedtotheannualpowerloadforecasting.Therefore,theGRNNwasusedforannualpowerloadforecastinginthisKeywords:paper.However,howtodeterminetheappropriatespreadparameterinusingtheGRNNforpowerloadAnnualp

5、owerloadforecastingforecastingisakeypoint.Inthispaper,ahybridannualpowerloadforecastingmodelcombiningfruitGeneralizedregressionneuralnetworkFruit?yoptimizationalgorithm?yoptimizationalgorithm(FOA)andgeneralizedregressionneuralnetworkwasproposedtosolvethisOptimizationproblemproblem,wher

6、etheFOAwasusedtoautomaticallyselecttheappropriatespreadparametervalueforParameterselectiontheGRNNpowerloadforecastingmodel.Theeffectivenessofthisproposedhybridmodelwasprovedbytwoexperimentsimulations,whichbothshowthattheproposedhybridmodeloutperformstheGRNNmodelwithdefaultparameter,GRN

7、Nmodelwithparticleswarmoptimization(PSOGRNN),leastsquaressupportvectormachinewithsimulatedannealingalgorithm(SALSSVM),andtheordinaryleastsquareslinearregression(OLS_LR)forecastingmodelsintheannualpowerloadforecasting.ó2012ElsevierB.V.Allrightsreserved.1.Introductionneeded.However,bec

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