• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.2
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• pp.16-22
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• 1983

In this paper, we obtained PFME(probability for maximum entropy) and entropy when a conditional probability was given in a binary list order Markov Information Source. And, when steady state probability was constant, the influence of change of a conditional probability on entropy was examined, too.

• The Mathematical Education
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• v.25 no.1
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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 Wind Energy
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• v.14 no.1
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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.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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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.

• Journal of the Korean Mathematical Society
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• v.33 no.4
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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)).

• Journal of information and communication convergence engineering
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• v.6 no.2
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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.

• Journal of applied mathematics & informatics
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• v.30 no.3_4
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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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.1-10
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• 2009

Bus delay time is occurred as the result of traffic condition and important factor to predict bus arrival time. In this paper, transition probability matrixes between bus stops are made by using Markov Chain and it is predicted bus delay time with them. As the results of study, it is confirmed a possibility of adapting the assumption which it has same bus transition probability between stops through paired-samples T-test and overcame the limitation of exiting studies in case there is no scheduled bus arrival time for each stops with using bus interval time. Therefore it will be possible to predict bus arrival time with Markov Chain.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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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.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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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.