基于对抗神经网络模型的中国铀资源可持续发展安全评价（英文）-豆柴文库

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基于对抗神经网络模型的中国铀资源可持续发展安全评价（英文）
TITLE:SustainableDevelopmentandSafetyAssessmentofChineseUraniumResourcesusingAdversarialNeuralNetworkModel
ABSTRACT:
Uraniumisacrucialresourceforthenuclearenergyindustry.However,thesustainabledevelopmentandsafetyassessmentofuraniumresourcesisanimportantissuethatrequirescriticalattention.Inthispaper,weproposeanadversarialneuralnetworkmodelforassessingthesafetyandsustainabilityofuraniumresourcesinChina.Theproposedmodelemploysbothageneratorandadiscriminatorneuralnetworkthatworktogethertoidentifyandmitigatepotentialhazards,evaluatesafety-criticaltrends,andpredictreliableestimatesoffutureresourcesupplyanddemand.Wevalidatetheproposedmodelusinghistoricaldataandexaminethemodel'seffectivenessinpredictinguraniumresourcedevelopment.TheresultsindicatethattheproposedadversarialneuralnetworkmodeliseffectiveinevaluatingthesustainabilityandsafetyofuraniumresourcedevelopmentinChina.
INTRODUCTION:
China,astheworld'slargestenergyconsumer,isheavilyreliantonnuclearenergy,whichimpliesasignificantdependenceonuraniumresources.However,thesafeandsustainabledevelopmentofuraniumresourcesisasignificantchallengethatrequirescarefulplanningandmanagement.Uraniumproductionisahazardousactivitythatrequirescarefulconsiderationofsafety,environmental,andsocioeconomicfactors.Theenergysector'ssustainabilityandsafetydependlargelyontheavailabilityofuraniumresources,whicharefinite,andtherisksassociatedwiththeirdevelopment,suchasenvironmentalpollutionandhealthhazards.Therefore,selectingasustainable,safe,andeconomicallyviableuraniumresourcedevelopmentstrategyiscriticalforChina'slong-termenergysecurity.
Inthispaper,weproposeanoveladversarialneuralnetworkmodelthataimstoevaluatethesustainabilityandsafetyofuraniumresourcedevelopmentinChina.Theproposedmodelemploysbothageneratorandadiscriminatorneuralnetworkthatusearangeofdatasourcestodetectpotentialhazardsandevaluatesafety-criticaltrends.Thegeneratornetworkgeneratessyntheticsamplesofuraniumresourcedatatotrainthediscriminatortorecognizep