• 한국수학교육학회지시리즈A:수학교육
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• 제25권1호
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• pp.1-8
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• 1986

It is a common saying that markov-chain is a special case of probability course. That is to say, It means an unchangeable markov-chain process of the transition-probability of discontinuous time. There are two kinds of ways to show transition probability parade matrix theory. The first is the way by arrangement of a rightangled tetragon. The second part is a vertical measurement and direction sing by transition-circle. In this essay, I try to find out existence of procession for transition-probability applied markov-chain. And it is possible for me to know not only, what it is basic on a study of chain but also being applied to abnormal problems following a flow change and statistic facts expecting to use as a model of air expansion in physics.

• Journal of applied mathematics & informatics
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• 제30권3_4호
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• pp.541-553
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• 2012

In this paper, we study some limit properties of the harmonic mean of random transition probability for a second-order nonhomogeneous Markov chain on the generalized gambling system indexed by a tree by constructing a nonnegative martingale. As corollary, we obtain the property of the harmonic mean and the arithmetic mean of random transition probability for a second-order nonhomogeneous Markov chain indexed by a double root tree.

• 풍력에너지저널
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• 제14권1호
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• pp.37-43
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• 2023

In this study, synthetic time series wind data was generated numerically using a second-order Markov chain. One year of wind data in 2020 measured by the AWS on Wido Island was used to investigate the statistics for measured wind data. Both the transition probability matrix and the cumulative transition probability matrix for annual hourly mean wind speed were obtained through statistical analysis. Probability density distribution along the wind speed and autocorrelation according to time were compared with the first- and the second-order Markov chains with various lengths of time series wind data. Probability density distributions for measured wind data and synthetic wind data using the first- and the second-order Markov chains were also compared to each other. For the case of the second-order Markov chain, some improvement of the autocorrelation was verified. It turns out that the autocorrelation converges to zero according to increasing the wind speed when the data size is sufficiently large. The generation of artificial wind data is expected to be useful as input data for virtual digital twin wind turbines.

• 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.

• 대한수학회지
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• 제33권4호
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• pp.983-992
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• 1996

Let p(x, dy) be a transition probability function on $(S, \rho)$, where S is a complete separable metric space. Then a Markov process $X_n$ which has p(x, dy) as its transition probability may be generated by random iterations of the form $X_{n+1} = f(X_n, \varepsilon_{n+1})$, where $\varepsilon_n$ is a sequence of independent and identically distributed random variables (See, e.g., Kifer(1986), Bhattacharya and Waymire(1990)).

• 대한수학회지
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• 제60권3호
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• pp.537-564
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• 2023

In this paper, we are mainly concerned with two-sided estimates for transition probabilities of symmetric Markov chains on ℤ^d, whose one-step transition probability is comparable to |x - y|^-dϕ_j (|x - y|)^-1 with ϕ_j being a positive regularly varying function on [1, ∞) with index α ∈ [2, ∞). For upper bounds, we directly apply the comparison idea and the Davies method, which considerably improves the existing arguments in the literature; while for lower bounds the relation with the corresponding continuous time symmetric Markov chains are fully used. In particular, our results answer one open question mentioned in the paper by Murugan and Saloff-Coste (2015).

• 한국군사과학기술학회지
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• 제2권2호
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• pp.131-139
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• 1999

An easy and efficient method is proposed for a computation of reliability of preprocessing filters in the fire control system when the sensor data are frequently unreliable depending on the operation environment. It computes state transition probability matrix after modeling filter states as a Markov process, and computing false alarm and detection probability of each filter state under the given sensor failure probability. It shows that two important indices such as distributed state probability and error variance can be derived easily for a reliability assessment of the given sensor fusion system.

• 한국정보통신학회논문지
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• 제8권5호
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• pp.1010-1019
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• 2004

본 논문에서는 Nakagami-m 페이딩 채널을 Finite-State Markov Channel (FSMC)로 모델링하고, 채널 상태 변화에 따른 통신 시스템의 성능을 분석하였다. 고려한 FSMC 모델에서는 수신 신호의 신호 대 잡음 전력비를 유한개의 구간으로 나눠 각각의 구간을 Markov 체인의 상태로 대응한다. 각 상태는 무기억 이진 대칭 통신로로 가정하고, 한 상태에서 다른 상태로의 천이는 Markov 천이를 따른다고 가정한다. 수치 해석을 통해 각 상태에 있어서의 평균 심볼 오율, 정상 상태 확률 그리고 상태 천이 확률을 구하여 FSMC 모델을 구성하였고, 상태 천이 지수를 변경함으로써 여러 페이딩 환경을 FSMC 모델로 나타낼 수 있음을 확인하였다. 상태 천이 지수가 클 경우인 빠른 페이딩 채널에서는 채널이 i.i.d. 특성을 나타내게 되며, 상태 천이 지수가 작을 경우인 느린 페이딩 채널은 인접한 상태로의 천이만 발생하는 간단한 FSMC 모델로 표현될 수 있음을 확인하였다. 마지막으로 제안한 FSMC 모델의 응용 예로써, 여러 채널 환경에서 랜덤 에러 정정 부호의 부호화 이득의 차이를 컴퓨터 시뮬레이션을 통해 비교, 분석하였다.

• 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.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.1-9
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• 2007

A three-state Markov logistic regression model is suggested to forecast the probability of tomorrow's precipitation based on the current meteorological situation. The suggested model turns out to be better than Markov regression model in the sense of the mean squared error of forecasting for the rainfall data of Seoul area.