基于cp某某的某某i某某-某p神经网络需求预测模型分析

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1、●k--4，’■，一东北大学硕士学位论文AbstractResearchONDemandForecastingModelofARIMA．BPNeuralNetworkBasedonCPFRAbstractInretailingindustry,CPFR(CollaborativePlanningForecastingandReplenishment)wasconsequentlyinitiatedtodownsizethesupplychainoperationcostsandincreasecustomer

2、satisfactionaswell．CPFRisdecidedtoimproveinternalandextemalcooperationefficiency,andlayafoundationforthefullintegrationofsupplychain．CPFRnotonlysavedthesupplychainoperationcosts，butincreasedthesalesaswell,andmoreimportant，ledtosupplychainintegrationbycontin

3、uouslyimprovingthepartner’Srelationshipandtrustlevelbyextendingcooperationscopefrominventorymanagementtodemandmanagement．Inter-enterprisecollaborativedemandforecastingisthecoreofCPFRimplementation,itimprovetheaccuracyofdemandforecasting．Andaccuratedemandfor

4、ecastingCalllowertheproductioncosts，transportationcostsandinventorycosts，Callincreasethesales，therebyimprovethesupplychainoperationefficiency．ThearticlestudiesforecastingmodelmainlybasedonAutoregressiveIntegratedMovingAverage(ARIMA)andBack—PropagationNetwor

5、k(BPNetwork)ofCPFR,onthebasisofsummingupthepast,whichtakesneedsas0bjectincludingsuppliersandmoreretailersoverthesupplychain，specificresearchcontains：(1)BasedoncollaborativeforecastingofCPFR，whichachievesinformationsharingbetweenthesuppliersandretailers,andg

6、uaranteestheaccuracyofforecastingdata,andrealizesunificationofpredictionmethodbetweenthetwoaccordingtoestablishingprojectteam，tothemaximumextent,reducesthepossibilityofpredictinganomalies．(2)Thesupplychaindemandofthestudy,neuralnetworkasaforecastingtool，gen

7、eticalgorithmasoptimizationtool，threeofthebasictheoryandprincipleoftheintegration．Afteroptimizedtheweightofneuralnetwork,theefficiencyoflearninggreatlyimproved．(3)Thisarticlewillbebothorganic：theUSCofARIMAmodelsequencesoflinearpredictionextractionofuncertai

8、nty,withtheremainingresidualcharacteristicsofthenonlinearimprovedBPneuralnetworkmodelusedinformationextraction，andestablishARIMA-BPforecastingmodel．Byallex锄plcthisarticlemakesaforecastingresultcomparis