• Title/Summary/Keyword: Markov probability

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이진 일차 Markov 정보원의 엔트로피에 관한 연구 (A Study on the Entropy of Binary First Order Markov Information Source)

  • 송익호;안수길
    • 대한전자공학회논문지
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    • 제20권2호
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    • pp.16-22
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    • 1983
  • 본 논문에서는 이진 일차 Markov 정보원에서 하나의 조건부 확률이 주어졌을 때, 엔트로피(entropy)를 최대로 하기 위한 나머지의 조건부 확률(PFME; probability for maximum entropy)과 그때의 언트로피를 구했다. 또한, 평형 상태 확률이 일정할 때 조건부 확률의 변화가 엔트로피에 미치는 영향도 함께 고찰하였다.

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Markov 연쇄를 적용한 확률지도연구 (A study of guiding probability applied markov-chain)

  • 이태규
    • 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.

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2차 마르코프 사슬 모델을 이용한 시계열 인공 풍속 자료의 생성 (Generation of Synthetic Time Series Wind Speed Data using Second-Order Markov Chain Model)

  • 유기완
    • 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.

Forecasting Probability of Precipitation Using Morkov Logistic Regression Model

  • Park, Jeong-Soo;Kim, Yun-Seon
    • 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.

LIMIT THEOREMS FOR MARKOV PROCESSES GENERATED BY ITERATIONS OF RANDOM MAPS

  • Lee, Oe-Sook
    • 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)).

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Performance Analysis of Channel Error Probability using Markov Model for SCTP Protocol

  • Shinn, Byung-Cheol;Feng, Bai;Khongorzul, Dashdondov
    • Journal of information and communication convergence engineering
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    • 제6권2호
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    • pp.134-139
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    • 2008
  • In this paper, we propose an analysis model for the performance of channel error probability in Stream Control Transmission Protocol (SCTP) using Markov model. In this model it is assumed that the compressor and decompressor work in Unidirectional Mode. And the average throughput of SCTP protocol is obtained by finding the throughputs of when the initial channel state is good or bad.

SOME LIMIT PROPERTIES OF RANDOM TRANSITION PROBABILITY FOR SECOND-ORDER NONHOMOGENEOUS MARKOV CHAINS ON GENERALIZED GAMBLING SYSTEM INDEXED BY A DOUBLE ROOTED TREE

  • Wang, Kangkang;Zong, Decai
    • 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.

Markov Chain을 이용한 버스지체시간 예측 (The Bus Delay Time Prediction Using Markov Chain)

  • 이승훈;문병석;박범진
    • 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.

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Markov process 및 상태천이확률 행렬 계산을 통한 사격통제장치 전처리필터 신뢰성 산출 기법 (A computation method of reliability for preprocessing filters in the fire control system using Markov process and state transition probability matrix)

  • 김재훈;유준
    • 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.

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A M-TYPE RISK MODEL WITH MARKOV-MODULATED PREMIUM RATE

  • Yu, Wen-Guang
    • Journal of applied mathematics & informatics
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    • 제27권5_6호
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    • pp.1033-1047
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    • 2009
  • In this paper, we consider a m-type risk model with Markov-modulated premium rate. A integral equation for the conditional ruin probability is obtained. A recursive inequality for the ruin probability with the stationary initial distribution and the upper bound for the ruin probability with no initial reserve are given. A system of Laplace transforms of non-ruin probabilities, given the initial environment state, is established from a system of integro-differential equations. In the two-state model, explicit formulas for non-ruin probabilities are obtained when the initial reserve is zero or when both claim size distributions belong to the $K_n$-family, n $\in$ $N^+$ One example is given with claim sizes that have exponential distributions.

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