简介：在文献[2]的基础上讨论Hilbert代数的Fuzzy理想,获得了Hilbert代数的Fuzzy理想的一些等价条件以及同态映射象的性质.

简介：引入了BCC-代数的BCC-关联理想、BCC-交换理想及BCC-正关联理想、FuzzyBCC-关联理想、FuzzyBCC-交换理想和FuzzyBCC-正关联理想等概念,并得到一些有趣的结果.

简介：ToimprovethecurrentGISfunctionsindescribinggeographicobjectswithfuzziness,thispaperbeginswithadiscussiononthedistancemeasureofspatialobjectsbasedonthetheoryofsetsandanintroductionofdilationanderosionoperators.Undertheassumptionthatchangesofattributesinageographicregionaregradual,theanalyticexpressionsforthefuzzyobjectsofpoints,linesandareas,andthedescriptionoftheirformalstructuresarepresented.Theanalyticmodelofgeographicobjectsbymeansoffuzzyfieldsisdeveloped.Wehaveshownthatthe9-intersectionmodelproposedbyEgenhoferandFranzosa(1991)isaspecialcaseofthemodelpresentedinthepaper.

简介：Thispaperpresentsanewfuzzymultiplecriteria(bothqualitativeandquantitative)decision-making(MCDM)methodbasedonfuzzyrelationaldegreeanalysis.Theconceptsoffuzzysettheoryareusedtoconstructaweightedsuitabilitydecisionmatrixtoevaluatetheweightedsuitabilityofdifferentalternativesversusvariouscriteria.Thepositiveidealsolutionandnegativeidealsolutionarethenobtainedbyusingamethodofrankingfuzzynumbers,andthefuzzyrelationaldegreesofdifferentalternativesversuspositiveidealsolutionandnegativeidealsolutionarecalculatedbyusingtheproposedarithmetic.Finally,therelativerelationaldegreesofvariousalternativesversuspositiveidealsolutionarerankedtodeterminethebestalternative.Anumericalexampleisprovidedtoillustratetheproposedmethodattheendofthispaper.

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简介：Aneuro-fuzzysystemmodelbasedonautomaticfuzzyclusteringisproposed.Ahybridmodelidentificationalgorithmisalsodevelopedtodecidethemodelstructureandmodelparameters.Thealgorithmmainlyincludesthreeparts:1)AutomaticfuzzyC-means(AFCM),whichisappliedtogeneratefuzzyrulesautomatically,andthenfixonthesizeoftheneuro-fuzzynetwork,bywhichthecomplexityofsystemdesignisreducesdgreatlyatthepriceofthefittingcapability;2)Recursiveleastsquareestimation(RLSE).ItisusedtoupdatetheparametersofTakagi-Sugenomodel,whichisemployedtodescribethebehaviorofthesystem;3)Gradientdescentalgorithmisalsoproposedforthefuzzyvaluesaccordingtothebackpropagationalgorithmofneuralnetwork.Finally,modelingthedynamicalequationofthetwo-linkmanipulatorwiththeproposedapproachisillustratedtovalidatethefeasibilityofthemethod.

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简介：Syllogisticfuzzyreasoningisintroducedintofuzzysystem,andthenewCascadedFuzzySystem(CFS)ispresented.ThethoroughlytheoreticalanalysisandexperimentalresultsshowthatsyllogisticfuzzyreasoningismorerobustthanallotherimplicationinferencesfornoisedataandthatCFShasbetterrobustnessthanconventionalfuzzysystems,whichprovidethesolidfoundationforCFS'spotentialapplicationinfuzzycontrolandmodelingandsoon.

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简介：研究了Fuzzy相等、Fuzzy线性相关、Fuzzy基,获得了单个向量Fuzzy线性相关当且仅当它是'零向量',两个向量Fuzzy线性相关当且仅当它们'成比例'以及象'替换定理'等许多相类似的性质;并且讨论了线性变换在Fuzzy基下的矩阵,获得了线性变换的和、数乘对应着Fuzzy矩阵的和与数乘.

简介：ThenotionsoffuzzydotidealsandfuzzydotH-idealsinBCH-algebrasareintro-duced,severalappropriateexamplesareprovided,andtheirsomepropertiesareinvestigated.Therelationsamongfuzzyideal,fuzzyH-ideal,fuzzydotidealandfuzzydotH-idealsinBCH-algebrasarediscussed,severalequivalentdepictionsoffuzzydotidealareobtained.Howtodealwiththehomomorphicimageandinverseimageoffuzzydotideals(fuzzydotH-ideals)arestudied.Therelationsbetweenafuzzydotideal(fuzzydotH-ideal)inBCH-algebrasandafuzzydotideal(fuzzydotH-ideal)intheproductalgebraofBCH-algebrasaregiven.

简介：Inthispaper,wegiveanorder-preserving,isometricandisomorphicembeddingoperatorfromthefuzzynumberspaceE~1toaclassicalBanachspaceandshowsomenecessaryandsufficientintegrabilityconditionsoffuzzyintegralswhichweredefinedbyM.MatlokaandO.Kalevabymeansofsuchanoperator.

简介：我们描述在模糊集合和代数学的亢奋的结构之间的关系。事实上，这篇论文是Davvaz介绍在的想法的继续(模糊集合Syst，117：477-484，2001)并且Bhakat和Das在(模糊集合Syst，80：359-368，1996)。有一个珍视间隔的模糊集合的模糊间隔价值的伪巧合的概念被介绍，这是在模糊集合的一个模糊的点的伪巧合的自然归纳。由使用这个新想法，这个概念珍视间隔(α，β)一个亢奋的模块的模糊sub-hypermodules被定义。这最新定义珍视间隔(α，模糊sub-hypermodule是的β)平常的模糊sub-hypermodule的归纳。我们将学习如此的模糊sub-hypermodules并且考虑一个亢奋的模块的基于含意的珍视间隔的模糊sub-hypermodules。

简介：Theanalytichierarchyprocess(AHP)isusedwidelyforanalyzingdecisionsmadeinvariousreal-worldapplications.Itsbasicideaistoconstructahierarchyofconceptsencounteredinagivendecisionproblemandtochoosethebestalternativeaccordingtopairwisecomparisonmatricesgivenbythedecisionmaker.Undertheassumptionoffullyrationaleconomics,areasonabledecisionshouldbeconsistent.Itbecomesanimportantissueonhowtoanalyzeandensuretheconsistencyofcomparisonmatricestogetherwiththejudgmentsofthedecisionmaker.Themainobjectivesofthepresentpaperarethreefold.First,wereviewthebasicideaandmethodsusedtodefinetheconsistencyandthetransitivityofmultiplicativereciprocalmatrices,additivereciprocalmatricesandcomparisonmatriceswithfuzzyintervalandtriangularfuzzynumbers.TheexistingcontroversybehindtheapplicationsoffuzzysettheorytotheAHPintheliteratureispresented.Second,theconsistencyofthecollectivecomparisonmatricesingroupdecisionmakingbasedonAHPandfuzzyAHPisfurtheranalyzed.WepointoutthattheweakconsistencyofpreferencerelationswithfuzzynumbersinfuzzyAHPandgroupdecisionmakingshouldbeinvestigatedcomprehensively.Third,undertheconsiderationofthevaguenessintheprocessofevaluatingthejudgements,anewconceptoffuzzyconsistencyofcomparisonmatricesintheAHPisgiven.

简介：Theinformationretrievalisoneofthecommonoperationsincomputerinformationsystems.Thispaperproposesakindofinformationretrievalmethodbasedonfuzzysettheory.

简介：Thispaperproposesanewneuralfuzzyinferencesystemthatmainlyconsistsoffourparts.Thefirstpartisabouthowtouseneuralnetworktoexpresstherelationwithinafuzzyrule.Thesecondpartisthesimplificationofthefirstpart,andexperimentsshowthatthesesimplificationswork.Onthecontrarytothesecondpart,thethirdpartistheenhancementofthefirstpartanditcanbeusedwhenthefirstpartcannotworkverywellinthefuzzyinferencealgorithm,whichwouldbeintroducedinthefourthpart.Finally,thefourthpart"neuralfuzzyinferencealgorithm"isbeenintroduced.Itcaninferencethenewmembershipfunctionoftheoutputbasedonpreviousfuzzyrules.Theaccuracyofthefuzzyinferencealgorithmisdependentonneuralnetworkgeneralizationability.Evenifthegeneralizationabilityoftheneuralnetworkweusedisgood,westillgetinaccurateresultssincethenewcomingrulemaynotberelatedtoanyofthepreviousrules.Experimentsshowthisalgorithmissuccessfulinsituationswhichsatisfytheseconditions.

简介：ThetypicalBDI(beliefdesireintention)modelofagentisnotefficientlycomputableandthestrictlogicexpressionisnoteasilyapplicabletotheAUV(autonomousunderwatervehicle)domainwithuncertainties.Inthispaper,anAUVfuzzyneuralBDImodelisproposed.Themodelisafuzzyneuralnetworkcomposedoffivelayers:input(beliefsanddesires),fuzzification,commitment,fuzzyintention,anddefuzzificationlayer.Inthemodel,thefuzzycommitmentrulesandneuralnetworkarecombinedtoformintentionsfrombeliefsanddesires.ThemodelisdemonstratedbysolvingPEG(pursuit-evasiongame),andthesimulationresultissatisfactory.

简介：Afaultdiagnosismodelisproposedbasedonfuzzysupportvectormachine(FSVM)combinedwithfuzzyclustering(FC).Consideringtherelationshipbetweenthesamplepointandnon-selfclass,FCalgorithmisappliedtogeneratefuzzymemberships.Inthealgorithm,sampleweightsbasedonadistributiondensityfunctionofdatapointandgeneticalgorithm(GA)areintroducedtoenhancetheperformanceofFC.Thenamulti-classFSVMwithradialbasisfunctionkernelisestablishedaccordingtodirectedacyclicgraphalgorithm,thepenaltyfactorandkernelparameterofwhichareoptimizedbyGA.Finally,themodelisexecutedformulti-classfaultdiagnosisofrollingelementbearings.Theresultsshowthatthepresentedmodelachieveshighperformancesbothinidentifyingfaulttypesandfaultdegrees.TheperformancecomparisonsofthepresentedmodelwithSVManddistance-basedFSVMfornoisycasedemonstratethecapacityofdealingwithnoiseandgeneralization.

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