简介:Wehavedevelopedafuzzyneuralexpertsystemthathastheprecisionandlearningabilityofaneuralnetwork.Knowledgeisacquiredfromdomainexpertsasfuzzyrulesandmembershipfunctions.Then,theyareconvertedintoaneuralnetworkwhichimplementsfuzzyinferencewithoutrulematching.Theneuralnetworkisappliedtoproblem-solvingandlearnsfromthedataobtainedduringoperationtoenhancetheaccuracy.Thelearningabilityoftheneuralnetworkmakesiteasytomodifythemembershipfunctionsdefinedbydomainexperts.Also,bymodifyingtheweightsofneuralnetworksadaptively,theproblemofbeliefpropagationinconventionalexpertsystemscanbesolvedeasily.Convertingtheneuralnetworkbackintofuzzyrulesandmembershipfunctionshelpsexplaintheinnerrepresentationandoperationoftheneuralnetwork.
简介:ThroughthepracticeofdevelopinganexpertsystemFBCDES(FeedBoxConceptualDe-signExpertSystem)fortheplanomillingmachineinCIMSERC(CIMSEngineeringResearchCenter)inChina,thepaperintendstointroduceacommonproblem-solvingstrategyforthemechanicalproductconceptualdesignexpertsystem.Meanwhilesomeproblemssuchassystemarchitecture,knowledgerepresentationsandinferenceenginesetsarealsodescribed.Ayetmoredetaileddiscussionisgiventothetechnicalproblemsforrealizingtwokeymodules,thatisconceptdesignmoduleandlayoutmodule.