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ConstructionofMilkPurchaseClassificationModelBasedon
ShuffledFrogLeapingAlgorithmandSupportVectorMachine
11,23,444
XIAOShijie,WANGQiaohua,LIChunfang,ZHAOLimei,LIUXinya,
43
LUShiyu,ZHANGShujun
（1.CollegeofEngineering,HuazhongAgriculturalUniversity,Wuhan430070,China;2.KeyLaboratoryofAgricul‐
turalEquipmentintheMid-LowerReachesoftheYangzeRiver,MinistryofAgricultureandRuralAffairs,Wuhan
430070,China;3.KeyLaboratoryofAnimalBreedingandReproductionofMinistryofEducation,HuazhongAgri‐
culturalUniversity,Wuhan430070,China;4.HebeiAnimalHusbandryAssociation,Shijiazhuang050031,China）
Abstract:Protein,fatandsomaticcellsarethreeimportantreferenceindicatorsinmilkpurchase,whichdeterminethequality
andpriceofmilk.Thetraditionalchemicalanalysismethodsoftheseindexesaretime-consumingandpollutetheenvironment,
whilethemid-infraredspectrumhastheadvantagesoffast,non-destructiveandsimpleoperation.Inordertorealizetherapid
classificationofmilkqualityandimprovetheproductionefficiencyofdairyenterprises,3216Holsteinmilksampleswerecho‐
senastheresearchobjectsandmid-infraredspectroscopytechnologywasappliedtorealizethedetectionandclassificationof4
differentqualitymilksduringthepurchaseprocess.Thespectrumwaspreprocessedbyusingthefirstderivativeandthefirstdif‐
ference,andcombinedwiththealgorithmcompetitiveadaptivereweightedsampling(CARS)andtheshuffledfrogleapingalgo‐
rithm(SFLA),theeffectivecharacteristicvariablesthatcouldrepresentdifferentmilkswereselected,andtheSVMmodelwas
established.Amongthem,thepenaltyparametercandthekernelfunctionparametergwhichwerethekeyparametersofthe
SVMmodelwereoptimizedbyusingthegridsearchmethod(GS),geneticalgorithm(GA)andparticleswarmalgorithm
(PSO).ThetrainingtimeofGS,GAandPSOalgorithmswerecompared,theresultsshowedthatthetrainingtimeofGSwas
muchlongerthanthatofGAandPSOalgorithms.TheSFLAalgorithmwasgenerallybetterthantheCARSalgorithm,andthe
PSOoptimizedtheSVMmodelthebest.Afterthefirst-orderdifferencepreprocessing,thePSO-SVMestablishedbyusingthe
SFLAalgorithmtofilterthecharacteristicvariables,theaccuracyofthetrainingset,theaccuracyofthetestsetandtheAUC
were97.8%,95.6%and0.96489,respectively.Thismodelhasahighaccuracyrateandhaspracticalapplicationvalueinthe
milkindustry.
Keywords:mid-infraredspectrum;milk;purchaseclassification;shuffledfrogleapingalgorithm;supportvectormachine
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