简介：针对系统动态可靠性中的不确定性问题,将动态故障树分析方法与模糊理论相结合,提出了基于模糊Markov过程的复杂系统动态可靠性仿真评估方法。首先,结合模糊理论与故障树方法,对基于模糊故障树的复杂系统可靠性模型进行了描述;其次,对动态故障树模型与的Markov过程模型的转换方法进行了研究,构建了复杂系统模糊动态可靠性评估模型,给出了系统模糊可靠度MonteCarlo仿真方法,并针对模糊隶属度难以求解的问题,结合目标规划模型,设计了动态隶属度确定算法;最后,以某型内燃机为例,对方法的科学性和有效性进行了验证。

简介：摘要本文针对现有教学效果评价方案的弊端，提出了基于Markov链和模糊数学的教学效果评价方法，该方法不仅不会忽视教师的纵向比较，反而能帮助教师很好地查找自己的缺点，使教师的工作不断得到完善和改进。

简介：根据随机过程原理与生命科学模型。简单的就业问题可以看作是具有两个瞬态的Markov过程．通过对就业转移概率、失业转移概率以及期望逗留期与就业强度和失业强度关系的研究，结果表明：就业转移概率和期望逗留期与就业强度具有相同的增减性。失业转移概率与失业强度的增减性则正好相反．

简介：就业率和就业质量是衡量中职教育教学水平的两大标准.利用MarkovChain评价法将就业质量划分不同等级,利用状态转移概率和由M.C.遍历性定理得出就业质量满足平稳分布.最后利用该分布确定就业质量的评价标准.文中旨在利用定量分析的手段对就业质量合理评价,从而提高中等职业教育的教学水平.

简介：本文主要在原有的G／G／1排队系统的模型中，引入“成批”到达的概念，引入一次到达人数的随机变量ξ，讨论忙期闲期有关的情况．并通过对模型的讨论解决了带有选择的排队过程的分布情况．

简介：以随机过程为研究工具研究了生物学中质体随细胞分裂而传递的规律,通过数学建模对含突变质体的杂合细胞的纯合概率和细胞的不同状态之间的转移在生物学意义上进行了详细的讨论.

简介：GivenanewDouble-MarkovriskmodelDM=(μ,Q,ν,H;Y,Z)andDouble-MarkovriskprocessU={U(t),t≥0}.Theruinorsurvivalproblemisaddressed.Equationswhichthesurvivalprobabilitysatisfiedandtheformulasofcalculatingsurvivalprobabilityareobtained.Recursionformulasofcalculatingthesurvivalprobabilityandanalyticexpressionofrecursionitemsareobtained.TheconclusionsareexpressedbyQmatrixforaMarkovchainandtransitionprobabilitiesforanotherMarkovChain.

简介：InthispaperareversibleMarkovprocessasachemicalpolymersreactionoftwotypesofmonomersisdefined.Byanalyzingthepartitionfunctionsoftheprocessweobtainthreedifferentdistributionsoftheaveragemolecularweight,dependingofthevalueofstrengthofthefragmentationreaction,andprovethatagelationoftheprocesswilloccurinthethermodynamiclimit.

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简介：TheauthorpresentssomestraightforwardproofsfortwocomparisontheoremsforGreenfunctionsofMarkovchains,whichslightlyimprovethepreviousresultsbyVaropoulos,DurrettandYanandChen.ArecentresultbyRogersandWilliamsaboutinstantaneousMarkovchainsisalsoimprovedbyusingthesameidea.

简介：<正>Inthispaper.wegivecharacterizationsofNashinequalitiesforbirth-deathprocessanddiffusionprocessontheline.Asaby-product.weprovethatfortheseprocesses.transienceimpliesthatthesemigroupsP（t）decayas‖P（t）‖1--x≤Ct-1.SufficientconditionsforgeneralMsrkovchainsarealsoobtained.

简介：1.IntrodnctionTheweightedMarkovdecisionprocesses(MDP’s)havebeenextensivelystudiedsince1980’s,seeforinstance,[1-6]andsoon.ThetheoryofweightedMDP’swithperturbedtransitionprobabilitiesappearstohavebeenmentionedonlyin[7].Thispaperwilldiscussthemodelsofwe...

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简介：Weraiseandpartlyanswerthequestion:whetherthereexistsaMarkovsystemwithrespecttowhichthezerosoftheChebyshevpolynomialsaredense,butthemaximumlengthofazerofreeintervalofthenthChebyshevpolynomialdoesnottendstozero.Wealsodrawtheconclu-tionthataMarkovsystem,underanadditionalassumption,isdenseifandonlyifthemaxi-mumlengthofazerofreeintervalofthenthassociatedChebyshevpolynomialtendstozero.

简介：在这篇论文，我们考虑Markov进程(X~∈(t)，Z~∈(t))相应于有小参数∈的一个微弱地联合的椭圆形的PDE系统>0。我们首先证明那(X~∈(t)，Z~∈(t))由联合方法有Feller连续性，然后证明那(X~∈(t)，Z~∈t))由收养的Lyapunov不平等有不变的措施μ~∈(·)。最后，当小参数∈趋于到零，我们为μ~∈(·)建立一个大偏差原则。

简介：SupposethatCisafinitecollectionofpatterns.ObserveaMarkovchainuntiloneofthepatternsinCoccursasarun.Thistimeisdenotedbyτ.Inthispaper,weaimtogiveaneasywaytocalculatethemeanwaitingtimeE(τ)andthestoppingprobabilitiesP(τ=τA)withA∈C,whereτAisthewaitingtimeuntilthepatternAappearsasarun.

简介：Inordertoovercomethedisadvantagesoflowaccuracyrate,highcomplexityandpoorrobustnesstoimagenoiseinmanytraditionalalgorithmsofcloudimagedetection,thispaperproposedanovelalgorithmonthebasisofMarkovRandomField(MRF)modeling.Thispaperfirstdefinedalgorithmmodelandderivedthecorefactorsaffectingtheperformanceofthealgorithm,andthen,thesolvingofthisalgorithmwasobtainedbytheuseofBeliefPropagation(BP)algorithmandIteratedConditionalModes(ICM)algorithm.Finally,experimentsindicatethatthisalgorithmforthecloudimagedetectionhashigheraverageaccuracyratewhichisabout98.76%andtheaverageresultcanalsoreach96.92%fordifferenttypeofimagenoise.

简介：这份报纸在线和其生成器承认空必要系列的出生鈥揹eath进程上为散开进程给描述。为为一般Markov发电机的空必要系列的一些相等的条件也被讨论。关键词Markov生成器-必要光谱-紧缩的嵌入-强壮的鈥搕ype不平等先生(2000)题目分类46E35-60J60-RFDP(号码2001002707)部分地支持的60J75研究，973工程，和NSFC(号码10121101)

简介：Regimeswitching,whichisdescribedbyaMarkovchain,isintroducedinaMarkovcopulamodel.Weprovethatthemarginals(X,H~i),i=1,2,3oftheMarkovcopulamodel(X,H)arestillMarkovprocessesandhavemartingaleproperty.Inthisproposedmodel,apricingformulaofcreditdefaultswap(CDS)withbilateralcounterpartyriskisderived.更多还原

简介：ThispaperexaminesrecentdevelopmentsandapplicationsofHiddenMarkovModels(HMMs)tovariousproblemsincomputationalbiology,includingmultiplesequencealignment,homologydetection,proteinsequencesclassification,andgenomicannotation.