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1、实用标准文案PredictionImpactofVacuumDryingParametersonRiceTasteValuewithNeuralNetworkModelXuZemin1,WuWenfu2,YinLiyan21.CollegeofBiologicalScienceandTechnology,ChangChunUniversity,ChangChun,130022,China;2.CollegeofBiologicalandAgriculturalEngineering,JilinU
2、niversity,ChangChun,130022,chinaAbstract:Processcontroloverricevacuumdryingdirectlyaffectsthetastequalityofdriedrice.Dryingtemperature,initialricemoisturecontentandvacuumdegreearethemainparametersthataffectrice-dryingprocess.Thispapermakesresearchont
3、hechangelawoftastequalityofbrownriceversusdryingparametersduringvacuumdryingprocessthroughestablishmentofneuralnetworkmodelbetweenbrownricetastevalueanddryingparameters,whichwillprovidereferenceforobjectiveevaluationonricetaste,driedricequalityandthe
4、designofvacuumdryer.Theresultsshowthat,BPneuralnetworkmodelpredictstheaveragerelativeerrorof2.88%,correlationcoefficientof0.96,BPneuralnetworkcanserveasanewmodelfordescriptionofricetastevalueofvacuumdrying.Keywords:neuralnetwork;rice;vacuumdrying;tas
5、tequality;model1IntroductionRiceisaheatsensitivematerialanditsdryingprocesscontrolisextremelyimportant.Ifthedryingparametersareinappropriate,ricequalitywillbeadverselyaffected.Howtorealizeartificialintelligencecontrolofvacuumdryingprocessisthekeytoen
6、surericetastequality[1-4].Thetasteisanimportantevaluationindexofricequality.Tastevalueisanindexthatreflectsthedegreeofricetaste,whichcanbemeasuredwithtasteanalyzer.Thelargertheindex,thebetterthetaste,withthemaximumvalueof100%.Tasteanalyzerisatastemea
7、suringinstrumentdevelopedbyJapanesescholarsbyestablishmentofrelationshipbetweenthetasteandthephysicalandchemicalindicatorsofricecontent(amylose,protein,moistureandfattyacids)basedontheoryneuro-fuzzy[5].Thepapermakescorrectanalysisonthemainfactorsthat
8、determinericetastebynearinfraredanalysismethodanddeterminesthetastevaluebasedontheaboveanalysisdataandthefunctionalvaluesmeasuredbyapplicationoffuzzytheoryandusingfoodtastemeasurementformularesolvedbyhumanneuralnetworkinformationprocessingsystem.2Mat
