简介：提出了一种基于粗集理论的教师导向性评价模型．与其他模型相比，该方法更简洁、科学、有效．

简介：利用Rough集理论给出了一种客观的概率分配函数,然后利用改进的证据理论提出了一种不确定性知识的特征识别方法.

简介：容差关系T定义为,x与之非对称相似的对象集合的定义为,Kryszkiewicz给出了容差关系的定义

简介：底层的wettability和粗糙在无柄的微滴的蒸发对接触角度和三阶段的接触线的进化关键。在这份报纸，由在nanoscale为微滴蒸发执行分子的动力学模拟，我们证明wettability比粗糙更重要。为光滑的底层，nanodroplet的蒸发行为在宏观的规模类似于那。这类似也在不平的吸水的底层的情况中被观察。为不平的恐水病的底层，然而，卡住的经常的接触角度和接触线在蒸发期间接着出现。这建议恐水病的底层的粗糙为蒸发技术在是有用的在nanoscale自己组装。

简介：Roughsetisanewapproachtouncertaintiesinspatialanalysis.Inthispaper,roughsetsymbolsaresimplifiedandstandardizedintermsofroughinterpretationandspecializedindication.Roughspatialentitiesandtheirtopologicalrelationshipsarealsoproposedinroughspace,thusauniversalintersectedequationisdeveloped,androughmembershipfunctionisfurtherextendedwiththegrayscaleinourcasestudy.Wecompletethreeworks.First,asetofsimplifiedroughsymbolsisadvancedonthebasisofexistingroughsymbols.Second,roughspatialentityisputforwardtostudytherealworldasitis,withoutforcinguncertaintiesintocrispset.Third,roughspatialtopologicalrelationshipsarestudiedbyusingroughmatrixandtheirfigures.Therelationshipsaredividedintothreetypes,crispentityandcrispentity(CC),roughentityandcrispentity(RC),androughentityandroughentity(RR).Auniversalintersectedequationisfurtherproposed.Finally,themaximumandminimummapsofriverthematicclassificationaregeneratedviaroughmembershipfunctionandroughrelationshipsinourcasestudy.

简介：Thisarticleisbasedonthenotionsofacongruenceofasemigroupandthep-lowerandp-upperapproximationsofanonemptysubsetofasemigroup,discussingsomepropertiesoftheproductofthesetwosubsetsaccordingtothepropertiesofsomeespecialsinglesubsetssuchassubsemigroupsandideals,thentherigorousproofwasgiven.Thustheroughtheoryinsemigroupsarecompletedandperfected.

简介：Inthissurveyreport,weshallmainlysummarizesomerecentprogress,interestingproblemsandtypicalmethodsusedinthetheoryrelatedtoroughMarcinkiewiczintegralsandroughsingularintegralsonproductspaces.Inaddition,wegivenewproofsforsomeknownresults.

简介：基于封面的不平的集合处理一盖住宇宙组织的数据。一个软集合是宇宙的子集的一个parameterized家庭。两个理论能处理数据的无常。软集合在对目标的近似描述上有并非任何限制，并且他们可能形成一盖住宇宙。从这个观点，我们建立在这二个理论之间的一个连接。明确地，我们为这个目的建议一个互补参数。与这个参数，软盖住近似空间被建立，二个理论是bridged.Furthermore，我们学习在盖住和软盖住近似空间之间的一些关系并且获得一些重要结果。最后，我们定义一个观点联合能帮助我们简化参数的集合并且减少一个软盖住近似空格的存储要求的参数。

简介：Inthispaper,theauthorgivestheweightedweakLipschitzboundednesswithpowerweightforroughmultilinearintegraloperators.Asimplewayisobtainedthatiscloselylinkedwithaclassofroughfractionalintegraloperators.

简介：在探讨粗糙集的概念及在某种程度上与许多其他处理含糊和不精确性等问题的基础上,讨论了相似模型在实践使用中具有比经典粗糙集更好的性能,描述与其他数学工具的结合,研究粗糙集理论目前比较引人注目的几个领域。

简介：粗糙集理论是一种新型的处理模糊和不确定知识的数学工具,已经在很多领域得到了广泛的应用.详细介绍了粗糙集理论的基本内容,并且给出了粗糙集理论在决策分析方面的一个应用实例,很好的证明了该理论的有效性.

简介：特征选择(FS)指选择给定的outcome.Unlike是很预兆的那些输入属性的过程另外的维数减小方法，在FS的reduction.The好处是双重的以后，特征选购者保存特征的原来的意思：它更加减少正式就职算法的跑的时间，并且增加在用模糊逻辑和模糊逻辑的乳房X线照片分类的FS过程基于的产生model.This纸分析的精确性Quickreduct算法被申请从特征的FS提取了使用在乳房X线照片region.The上构造的灰色的水平co-occurence矩阵(GLCM)预兆的精确性特征用NaiveBayes，Ripper，C4.5，和蚂蚁矿工algo被测试

简介：Inthecontextoftowermeasuredradiationdatasets.followingthecorrectionprinciplemeetingadiagnosticequationindataqualitycontrolandintermsofatechniqueformodelconstructionondataandANN(artificialneuralnetwork)retrievalforBPcorrectionofradiationmeasurementswithrougherrorsavailable,aBPmodelispresented.Evidencesuggeststhatthedevelopedmodelworkswellandissuperiortoaconvenientmultivariatelinearregressionmodel,indicatingitswideapplications.

简介：在这份报纸，我们学习概括Marcinkiewicz不可分的操作员M，产品空间n上的r???????????????椠獮湥楳楴楺杮吗？？

简介：Thankstothedevelopmentofmetallographicandopticaltechniques,thequantitativecharacterisationofthegeometryofroughsurfaceshasbecomeveryusefulinpracticalapplications.Today,numerousdifferentmethodsareavailablefordeterminingthreedimensionalco-ordinates,linearprofilesorheightcontourstoareasonabledegreeofaccuracyandwithinanacceptabletimeframe,andforevaluatingsuchdata.Inthisarticle,theuseofsuchtechniquesinthefieldoffractographyisdemonstratedwithreferencetoanumberofcasestudiesdealtwithbytheauthor'sownteam,supplementedbyseveralexamplesfromotherresearchgroups.Thefollowingexamplesarediscussed:Inaceramicmaterialdifferentfracturepathswerediscernedcorrespondingtodifferenttesttemperatures.Inhardmetals,itwasshownthathoththesub-criticalandsupercriticalpropagationofcracksoccurreddalongthesamepath.Frommeasurementsoftheproportionoffracturesurfacesoccurringalongandinthevariousdifferentphasespresentandthedepthofdimplesoccurringduringductilefractureinthebinderphase,thefractureenergyofEC-Co-hardalloyswithdifferentcobaltcontentsandtungstencarbidegrainsizeswascalculatedandfoundtobeinexcellentagreementwithactualexperimentalresults.Inthecaseofceramicfibre-aluminiummatrixcpmpositematerials,bymeasuringthebeightdistributionofthepositionsoffractureofthefibres,theloadtransferintheregionofthefracturesurfacewasdetermined.withthisinformationamodelwasdevelopedwhichexplainsthesignificantvariationinstrengthofthesematerialsFinally,amodelwasdevelopedformetallicmaterialsusingwhich,fromtheexperimentallydetermineddistributionsoftheheightandinclinationofthefracturefacets,thestressintensityofroughnessinducedcrackclosingcouldheaccuratelypredicted.

简介：<正>Inthispaper,westudythebifurcationproblemsofroughheteroclinicloupscormectingthrecsaddlepointsforahigher-dimensionalsystem.Undersometransversalconditionsandthenontwistedcondition.theexistence.uniqueness.ndincoexistenccofthcl-heteroclinicloopwiththrecortwosaddlepomts.l-homoclinicorbitandl-periodicorbitnearTareobtained.Nleanwhile,thebifurcationsurfacesandexistenceregionsarealsogiven.Moreover.theabovebifurcationresultsareextendedtothecaseforheteroclinicloopwithlsaddlepoints.

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简介：quasistatic一致设计被做为不平表面的粘附描绘有效连贯的地区行为。在一致设计的上下文，为一个不平的接口的一致连贯的地区(HCZ)的拖拉对分离关系能在显微镜的粘附和decohesion进程期间由于不稳定性是高度摆动的。不稳定性被发现不仅个别地而且一起发生在粘合剂之中微粗糙的接触，导致广泛的精力驱散。基于HCZ关系的行为，为在不平表面的粘附描述导致不稳定性的精力驱散的一个框架被建议阐明明显的接口粘附上的粗糙的效果。二个非维的参数，与粗糙形态学有关的伪和与aw分发有关的n，被识别为控制精力驱散很关键。为浅粗糙和强壮的内在的粘合剂力量的一个接口，如果我们使它更不平，接口粘附能更强壮(减少伪)或降低它的aw密度(增加的n)。HCZ设计方法能潜在地被扩大并且采用了为与多尺度的浅粗糙设计表面从内在的粘附性质衔接明显的粘附。

简介：Thispaperintroducesbackgroundofroughsettheory,thenproposesanewalgorithmforfindingoptimalreductionandmakecomparisonbetweentheoriginalalgorithmandtheimprovedonebytheexperimentabouttheninestandarddatasetinULdatabasetoexplainthevalidityoftheimprovedheuristicalgorithm.

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