简介：TheconceptofF-knowledgeispresentedbyemployingS-roughsets.ByengraftingandpenetratingbetweentheF-knowledgegeneratedbyS-roughsetsandtheRSAalgorithm,thesecuritytransmissionandrecognitionofmulti-agentF-knowledgeareproposed,whichincludesthesecuritytransmissionofmulti-agentF-knowledgewithpositivedirectionsecretkeyandthesecuritytransmissionofmulti-agentF-knowledgewithreversedirectionsecretkey.Finally,therecognitioncriterionandtheapplicationsofF-knowledgearepresented.ThesecurityofF-knowledgeisanewapplicationresearchdirectionofS-roughsetsininformationsystems.

简介：Whentheclassicalconstantfalse-alarmrate(CFAR)combinedwithfuzzyC-means(FCM)algorithmisappliedtotargetdetectioninsyntheticapertureradar(SAR)imageswithcomplexbackground,CFARrequiresblock-by-blockestimationofcluttermodelsandFCMclusteringconvergestolocaloptimum.Toaddresstheseproblems,thispaperpro-posesanewdetectionalgorithm:knowledge-basedcombinedwithimprovedgeneticalgorithm-fuzzyC-means(GA-FCM)algorithm.Firstly,thealgorithmtakestargetregion’smaximumandaverageintensity,area,lengthoflongaxisandlong-to-shortaxisratiooftheexternalellipseasfactorswhichinfluencethetargetappearingprobability.Theknowledge-baseddetectionalgorithmcanproducepreprocessresultswithouttheneedofestimationofcluttermodelsasCFARdoes.AfterwardtheGA-FCMalgorithmisimprovedtoclusterpre-processresults.IthasadvantagesofincorporatingglobaloptimizingabilityofGAandlocaloptimizingabilityofFCM,whichwillfurthereliminatefalsealarmsandgetbetterresults.TheeffectivenessoftheproposedtechniqueisexperimentallyvalidatedwithrealSARimages.

简介：Thispaperstudiesthelinkageproblembetweentheresultofhigh-levelsynthesisandback-endtechnology,presentsamethodofhigh-leveltechnologymappingbasedonknowledge,andstudiesdeeplyallofitsimportantlinkssuchasknowledgerepresentation,knowledgeutilityandknowledgeacquisition.Itincludes:(1)presentakindofexpandedproductionaboutknowledgeofcircuitstructure;(2)presentaVHDL-basedmethodtoacquireknowledgeoftechnologymapping;(3)providesolutioncontrolstrategyandalgorithmofknowledgeutility;(4)presentahalf-automaticmaintenancemethod,whichcanfindredundanceandcontradictionofknowledgebase;(5)presentapracticalmethodtoembedthealgorithmintoknowledgesystemtodecreasecomplexityofknowledgebase.Asystemhasbeendevelopedandlinkedwiththreekindsoftechnologies,soverifiedtheworkofthispaper.

简介：Toolmanagementisnotasingle,simpleactivity,itiscomprisedofacomplexsetoffunctions,especiallyinaflexiblemanufacturingsystem(FMS)environment.Theissuesassociatedwithtoolmanagementincludetoolrequirementplanning,toolreal-timescheduling,toolcribmanagement,toolinventorycontrol,toolfaultdiagnosis,tooltrackingandtoolmonitoring.Inordertomaketoolsflowinto/outofFMSefficiently,thisworkisaimedtodesignaknowledge-baseddecisionsupportsystem(KBDSS)fortoolmanagementinFMS.Firstlyanoverviewoftoolmanagementfunctionsisdescribed.ThenthestructureofKBDSSfortoolmanagementandtheessentialagentsinthedesignofKBDSSarepresented.FinallytheindividualagentsofKBDSSarediscussedfordesignanddevelopment.

简介：Inthispaper,weproposeaknowledgediscoverymethodbasedonthefuzzysettheorytohelpelderswithplantcultivation.Initially,thefuzzysetsareconstructedbyusingthefeatureselectionandstatisticalintervalestimation.Themin-maxinferenceandthecenterofgravitydefuzzificationmethodarethenusedtooutputacandidatepatternset.Finally,apatterndiscoveryisadoptedtoobtainthepatternsfromthecandidatesetforthecultivationsuggestionsbyconsideringthefrequencyweightanduser’sexperience.Inordertodemonstratetheperformanceofourmethodinplantingsystems,weconductaclicks-and-mortarcultivationplatform,namelyEdenGarden,fortheelderlylifestylesofhealthandsustainability(LOHAS).Theexperimentalresultsshowthattheaccuracyrateofourknowledgediscoverymethodcanreachupto85%.Moreover,theresultsoftheLOHASindexscaletablepresentthatthehappinessoftheeldersisincreasingwhiletheeldersareusingourproposedmethod.