• Journal of the Korean Statistical Society
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• 제28권4호
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• pp.515-522
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• 1999

A repair process of a system consisting of both perfect repairs and minimal repairs is introduced. The type of repair, when the system fails, is determined by an embedded two state Markov chain. We study several stochastic properties of the process including the preservation of ageing properties and the monotonicities of the time between successive repairs. After assigning repair costs to the process, we also show that an optimal repair policy uniquely exists, if the underlying life distribution of the system has DMRL.

• Journal of applied mathematics & informatics
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• 제37권5_6호
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• pp.469-480
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• 2019

A generalized tiling is defined as a generalization of the properties of tiling a region of ${\mathbb{Z}}^2$ with dominoes, and comprises tiling with rhombus and any other tilings that admits height functions which can be ordered into a distributive lattice. By using properties of the distributive lattice, we prove that the Markov chain consisting of moving from one height function to the next by a flip is fast mixing and the mixing time ${\tau}({\epsilon})$ is given by ${\tau}({\epsilon}){\leq}(kmn)^3(mn\;{\ln}\;k+{\ln}\;{\epsilon}^{-1})$, where mn is the area of the grid ${\Gamma}$ that is a k-regular polycell. This result generalizes the result of the authors (T-tetromino tiling Markov chain is fast mixing, Theor. Comp. Sci. (2018)) and improves on the mixing time obtained by using coupling arguments by N. Destainville and by M. Luby, D. Randall, A. Sinclair.

• 한국ITS학회 논문지
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• 제8권3호
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• pp.1-10
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• 2009

버스지체시간은 버스노선의 교통여건이 반영되어 나타나는 결과로서 버스도착시간을 예측하는데 있어 중요한 요소이다. 이에 본 연구에서는 다양한 변수를 사용하지 않아도 되는 마코브 체인을 이용하여 분석 정류장간 전이확률행렬표를 생성하고 이를 이용하여 버스지체시간을 예측하였다. 본 연구를 통하여 기존연구의 한계점인 정류장별 계획된 버스도착 시간이 존재하지 않은 경우에 대하여 배차시간을 이용한 버스지체시간 산출방법을 제시함으로서 기존연구의 한계점을 극복하였으며, 또한 정류장별 버스지체시간을 예측하기 위해 정의한 정류장간 버스지체의 전이는 동질하다는 귀무가설을 대웅표본 T검정을 통하여 채택함으로서 사용한 가정이 95% 신뢰수준에서 유의하다는 것을 확인하였다. 이를 통하여 향후마코브 체인을 이용하여 버스도착시간 예측이 가능할 것으로 판단된다.

• 통합자연과학논문집
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• 제7권3호
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• pp.200-207
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• 2014

Average number of samples to signal (ANSS) and average time to signal (ATS) are the most widely used criterion for comparing the efficiencies of the quality control charts. In this study the method of evaluating ANSS and ATS values of the multivariate exponentially weighted moving average (EWMA) control charts with Markov chain approach was presented when the production process is in control state or out of control state. Through numerical results, it is found that when the number of transient state r is less than 50, the calculated ANSS and ATS values are unstable; and ATS(r) tends to be stabilized when r is greater than 100; in addition, when the properties of multivariate EWMA control chart is evaluated using Markov chain method, the number of transient state r requires bigger values when the smoothing constatnt ${\lambda}$ becomes smaller.

• Journal of applied mathematics & informatics
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• 제24권1_2호
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• pp.505-511
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• 2007

In this paper, we examine the Markov chain $\{X_k,\;N_k;\;k=0,\;1,...$. We show that the marginal steady state distribution of Xk is discrete phase type. The implication of this result is that the queue length distribution of phase type for large number of examples where this Markov chain is applicable and shows a queueing application by matrix geometric methods.

• Industrial Engineering and Management Systems
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• 제15권2호
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• pp.131-142
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• 2016

We consider a multi-server queueing system without buffer and with two types of customers as a model of operation of a mobile network cell. Customers arrive at the system in the marked Markovian arrival flow. The service times of customers are exponentially distributed with parameters depending on the type of customer. A part of the available servers is reserved exclusively for service of first type customers. Customers who do not receive service upon arrival, can make repeated attempts. The system operation is influenced by random factors, leading to a change of the system parameters, including the total number of servers and the number of reserved servers. The behavior of the system is described by the multi-dimensional Markov chain. The generator of this Markov chain is constructed and the ergodicity condition is derived. Formulas for computation of the main performance measures of the system based on the stationary distribution of the Markov chain are derived. Numerical examples are presented.

• 경영과학
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• 제10권2호
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• pp.27-42
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• 1993

Markov chain models can be used to predict the state of the system in the future. We extend the existing Markov chain models in two ways. For the stationary model, we propose a procedure that obtains the transition probabilities by appling the empirical Bayes method, in which the parameters of the prior distribution in the Bayes estimator are obtained on the collaternal micro data. For non-stationary model, we suggest a procedure that obtains a time-varying transition probabilities as a function of the exogenous variables. To illustrate the effectiveness of our extended models, the models are applied to the macro and micro time-series data generated from actual survey. Our stationary model yields reliable parameter values of the prior distribution. And our non-stationary model can predict the variable transition probabilities effectively.

• Journal of the Korean Statistical Society
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• 제25권3호
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• pp.313-336
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• 1996

In this paper we consider weak convergence of some rescaled transi-tion probabilities of a real-valued, k-th order (k $\geq$ 1) stationary Markov chain. Under the assumption that the joint distribution of K + 1 consecutive variables belongs to the domain of attraction of a multivariate extreme value distribution, the paper gives a sufficient condition for the weak convergence and characterizes the limiting distribution via the multivariate extreme value distribution.

• Communications for Statistical Applications and Methods
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• 제21권2호
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• pp.135-145
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• 2014

The present study surveys Bayesian modeling structure for inferences about transition probabilities of Markov chain. The motivation of the study came from the data that shows transitional behaviors of emotionally disturbed children undergoing residential treatment program. Dirichlet distribution was used as prior for the multinomial distribution. The analysis with real data was implemented in WinBUGS programming environment. The performance of the model was compared to that of alternative approaches.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권4호
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• pp.313-322
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• 2016

Purpose: We introduce ways to employ Markov chain model to evaluate the effect of preventive maintenance process. While the preventive maintenance process decreases the failure rate of each subsystems, it increases the downtime of the system because the system can not work during the maintenance process. The goal of this paper is to introduce ways to analyze this trade-off. Methods: Markov chain models are employed. We derive the availability of the system consisting of N repairable subsystems by the methods under various maintenance policies. Results: To validate our methods, we apply our models to the real maintenance data reports of military truck. The error between the model and the data was about 1%. Conclusion: The models developed in this paper fit real data well. These techniques can be applied to calculate the availability under various preventive maintenance policies.