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基于遗传算法的曲面拟合参数辨识 Introduction Surfacefittingalgorithmisusedtoapproximatethegivendatapointsusingasurfacerepresentationsuchthatitcloselymatchesthepatternofthosepoints.Asurfaceinmathematicaltermsisgenerallydefinedbyasetofparametersthatareusedtodefineit.Oneofthemainchallengesofsurfacefittingalgorithmistoidentifytheseparametersaccurately.Inthispaper,wepresentasurfacefittingalgorithmbasedongeneticalgorithmthatidentifiestheparametersforeffectivelyfittingacurve. GeneticAlgorithm Geneticalgorithm(GA)isoneoftheheuristicoptimizationtechniques,inspiredbythenaturalselectionprocessesofbiologicalevolution.Itfollowstheprincipleofsurvivalofthefittest,wherethebest-fitindividualssurviveandareusedtogeneratethenextgeneration.Thealgorithmconsistsofapopulationofindividuals,eachhavingasetofgenesthatrepresentthesolutiontoagivenoptimizationproblem.Theseindividualsundergoselection,crossover,andmutationtogeneratethenextgenerationofindividuals.Thisprocessiscontinueduntilasatisfactorysolutionisreached. SurfaceParameterIdentification Insurfacefitting,theparametersusedtodescribethesurfacerepresentthebaseequationofthecurve.Thecurvefittingprocessinvolvesminimizingthedifferencebetweenthedatapointsandthesurfacemodel.Thesuitableparametersforthesurfacemodelareidentifiedusingthegeneticalgorithmusingthefollowingprocedure: 1.Initialization:Asetofrandomparametervaluesaregeneratedtocreatetheinitialpopulationofindividuals. 2.Evaluation:Eachindividualinthepopulationisevaluatedusinganobjectivefunction.Theobjectivefunctionisusedtodeterminethefitnessoftheindividual.Theobjectivefunctionforcurvefittingisthesumofthesquarederrorsbetweenthedatapointsandthesurfacemodelsgeneratedbytheindividual. 3.Selection:Thefittestindividualsinthepopulationareselectedtobecomeparentsforthenextgeneration.Theselectionprocessisbasedonthefitnessoftheindividual.Theindividualswithhigherfitnesshaveahigherprobabilityofbeingselectedasparents. 4.Crossover:Theparentsarecrossedovertogeneratetheoffspringforthenextgeneration.Thisprocessiscarriedoutb