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1、ApplIntell(2011)34:2846DOI10.1007/s10489-009-0177-8HybridcreditrankingintelligentsystemusingexpertsystemandartificialneuralnetworksArashBahrammirzaee·AliRajabzadehGhatari·ParvizAhmadi·KuroshMadaniPublishedonline:3April2009©SpringerScience+BusinessMedia,LLC2009AbstractT
2、hemaingoalofallcommercialbanksistocol-KeywordsHybridintelligentsystem·Neuralnetwork·lectthesavingsoflegalandrealpersonsandallocatethemExpertsystem·Creditrankingascredittoindustrial,servicesandproductioncompanies.Nonrepaymentofsuchcreditscausemanyproblemstothebankssuch
3、asincapabilitytorepaythecentralbanksloans,1IntroductionincreasingtheamountofcreditallocationscomparingtocreditrepaymentandincapabilitytoallocatemorecreditsNowadays,bankingsectorplaysveryimportantroleinthetocustomers.Theimportanceofcreditallocationinbank-economicandthe
4、socialwelfareofmanydevelopingcoun-ingindustryanditsimportantroleineconomicgrowthandtrieswithrelativelywell-privatizedeconomies.Banksgrantemploymentcreationleadsthedevelopmentofmanymodelscredittosupportmanufacturing,agricultural,commercialtoevaluatethecreditriskofappli
5、cants.Butmanyoftheseandserviceenterprises.These,inturn,providejobsthusmodelsareclassicandareincapabletodocreditevaluationamelioratingpurchasingpower,consumption,andsavings.completelyandefficiently.Thereforethedemandtousear-Itisthereforenecessarythatcreditgrantingbemade
6、ascor-tificialintelligenceinthisfieldhasgrownup.Inthispaperrectlyaspossiblewhilekeepingthedecisionmakingprocessafterprovidingappropriatecreditrankingmodelandcol-bothefficientandeffective.Amongthedifferentbankinglectingexpertsknowledge,wedesignahybridintelligentrisks,cred
7、itriskhasapotentialsocialimpactbecauseofsystemforcreditrankingusingreasoning-transformationalthenumberanddiversityofstakeholdersaffected.Businessmodels.Expertsystemassymbolicmoduleandartificialfailuresaffectshareholders,managers,lenders(banks),sup-neuralnetworkasnon-sy
8、mbolicmodulearecomponentsofpliers,clients,thefinancialcommunity,government,com-thishybridsystem.Suchmodelsprovidetheuniquefea
