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1、Team#15263Page21of23Leaves_Classification_and_Leaf_Mass_EstimationLeavesClassificationandLeafMassEstimationSummaryForthefirstproblem,weestablishourneuralnetworkmodeltoclassifyleavesoftreesbytakingeightcharacteristicsofleafintoconsideration.Theeightcharacte
2、risticsconsistofsawtoothnumber,petiolelength,bladelength,bladewidth,bladethickness,leafareaandcirculardegree.Ourresultsaresummarizedinaconclusionthatweclassifyleavesintofourteentypesincludinglinear,lanceolate,oblanceolate,spatulate,ovat,obovate,elliptic,ob
3、long,deltoid,reniform,orbicular,peltate,perfoliateandconnate.Ourneuralnetworkimplementtheclassificationtaskreliablyandcorrectly.Forthesecondproblem,wesetupourAHPmodeltofigureoutthereasonswhyleaveshavethevariousshapesandcometoaconclusionthatgene,auxin,clima
4、teanddiseasearethemainreasonswhichleadtovariousshapes.Forthethirdproblem,wediscussthisissuefromtheperspectiveofgrowthevolutionaryandhormones,buildcellsmechanicmodeltosolvethisproblemandsumuptheconclusionthattheshapesareinclinedtominimizeoverlappingindividu
5、alshadowsthatarecastsoastomaximizeexposure.Theshapeiseffectedbythedistributionofleaveswithinthevolumeofthetreeanditsbranches.Forthefourthproblem,weusestatisticalanalysisknowledgetoanalysethedataamongtreeprofiles,branchingstructureandleafshapes,aftermathema
6、ticallyanalyzing,finallyfindthatleavesshapeshaveadirectrelationwiththetreeprofileandbranchingstructure,Forthefifthproblem,weformulateourvolumetricmethodforleafmassestimationandlinearregressionmodelforseekingandcomparingthecorrelationbetweentheleafmassandtr
7、eeheight,treemassandcrownvolume.Weobtainthatcrownvolumehasthehighestcorrelationwithtreeleafmass.Sowemakeuseofthecrownvolumetoestimatetheleafmass.Atlast,wewriteonepagesummarysheetofourkeyfindings.Keywords:neuralnetwork,leafclassification,leafmassestimation,
8、AHP,leafshape,volumetricmethod,linearregressionmodelI.Team#15263Page21of23Leaves_Classification_and_Leaf_Mass_EstimationContentsContents0Ⅰ.Introduction1Ⅱ.SomeDefinitions1Ⅲ.GeneralAssumptions1Ⅳ.Symbols2Ⅴ.Probl
