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1、Team#15263Page21of23Leaves_Classification_and_Leaf_Mass_EstimationLeavesClassificationandLeafMassEstimationSummaryForthefirstproblem,weestablishourneuralnetworkmodeltoclassifyleavesoftreesbytakingeightcharacteristicsofleafintoconsideration.Theeightcharacteristicsconsistofsawto
2、othnumber,petiolelength,bladelength,bladewidth,bladethickness,leafareaandcirculardegree.Ourresultsaresummarizedinaconclusionthatweclassifyleavesintofourteentypesincludinglinear,lanceolate,oblanceolate,spatulate,ovat,obovate,elliptic,oblong,deltoid,reniform,orbicular,peltate,pe
3、rfoliateandconnate.Ourneuralnetworkimplementtheclassificationtaskreliablyandcorrectly.Forthesecondproblem,wesetupourAHPmodeltofigureoutthereasonswhyleaveshavethevariousshapesandcometoaconclusionthatgene,auxin,climateanddiseasearethemainreasonswhichleadtovariousshapes.Forthethi
4、rdproblem,wediscussthisissuefromtheperspectiveofgrowthevolutionaryandhormones,buildcellsmechanicmodeltosolvethisproblemandsumuptheconclusionthattheshapesareinclinedtominimizeoverlappingindividualshadowsthatarecastsoastomaximizeexposure.Theshapeiseffectedbythedistributionofleav
5、eswithinthevolumeofthetreeanditsbranches.Forthefourthproblem,weusestatisticalanalysisknowledgetoanalysethedataamongtreeprofiles,branchingstructureandleafshapes,aftermathematicallyanalyzing,finallyfindthatleavesshapeshaveadirectrelationwiththetreeprofileandbranchingstructure,Fo
6、rthefifthproblem,weformulateourvolumetricmethodforleafmassestimationandlinearregressionmodelforseekingandcomparingthecorrelationbetweentheleafmassandtreeheight,treemassandcrownvolume.Weobtainthatcrownvolumehasthehighestcorrelationwithtreeleafmass.Sowemakeuseofthecrownvolumetoe
7、stimatetheleafmass.Atlast,wewriteonepagesummarysheetofourkeyfindings.Keywords:neuralnetwork,leafclassification,leafmassestimation,AHP,leafshape,volumetricmethod,linearregressionmodelI.Team#15263Page21of23Leaves_Classification_and_Leaf_Mass_EstimationContentsContents0Ⅰ.Introduc
8、tion1Ⅱ.SomeDefinitions1Ⅲ.GeneralAssumptions1Ⅳ.Symbols2Ⅴ.Probl
