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基于ANN的结构可靠度分析方法.docx

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基于ANN的结构可靠度分析方法 Abstract: ArtificialNeuralNetworks(ANNs)havefoundapplicationinmanyfieldsofengineering,includingstructuralengineering.Ithasbeenusedforanalyzingthereliabilityofstructures,specificallytodealwiththeuncertaintiespresentintheprocess.ThispaperpresentsanoverviewoftheapplicationofANNinreliabilityanalysisofstructures.Itdiscussesthevarioustypesofneuralnetworksusedforthepurposeofstructuralreliabilityanalysis,themethodologyadoptedandsomeoftheapplicationsoftheANNapproach. Introduction Thereliabilityofstructuresisanimportantfactorforthesafetyofpeopleandtheirpossessions.Structuralfailurecancauselossoflife,damagetopropertyandenvironmentalpollution.Therefore,itisessentialtocarryoutreliabilityanalysisofstructurestoensurethesafedesignofstructures. Traditionally,themethodsofreliabilityanalysishavebeenbasedondeterministicanalyticalmodels,whichrequirepreciseinformationontheinputvariables.However,inpractice,therearealwaysuncertaintiesassociatedwiththeinputvariables.Theinputvariablesmaybesubjectedtorandomvariationscausedbymanufacturingtolerances,orthevariationmaybeduetofluctuationsintheenvironmentalconditions.Theseuncertaintiesaffectthereliabilityofthestructure,makingitdifficulttopredictthetruefailureprobabilityofthestructure. Toaddresstheseuncertainties,ArtificialNeuralNetworks(ANNs)havebeenusedforanalyzingthereliabilityofstructures.ANNsarewidelyusedinmanyfieldsofengineeringduetotheircapabilitytohandlecomplexnon-linearrelationshipsbetweeninputandoutputvariables. ApplicationofANNinStructuralReliabilityAnalysis ANNsprovideaneffectivemethodforthestructuralreliabilityanalysisofsystemsthathavecomplexbehavior.TheANNapproachdoesnotexplicitlymodeltheprobabilisticbehaviorofstructuralcomponents.Instead,itapproximatesthesebehaviorsusingdata-drivenapproachesthatlearnfromlargedatasets.ThemethodologyusedintheANNapproachcanbedividedintothreestages:(i)creationandtrainingoftheANNmodel,(ii)determinationofthereliabilityindex,and(iii)evaluationofthereliabilityofthesystem. CreationandTrainingof