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.
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.