• Proceedings of the KSR Conference
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• 2004.10a
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• pp.539-544
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• 2004

In this paper, we present reliability modeling and analysis method of the Automated Guideway Transit(AGT) vehicle system using analytical models, based on Markov Chains. The Markov model can express state transition of the AGT vehicle sys. that is considered to be in one of four states, such as basic operating (0), minor delay(1), major delay(2) and non-operating(3) state. The proposed Markov model is illustrated with a numerical example and cases to find a steady state availability, MTBF(mean time between failures), and MTTR(mean time to repair) under specified failure and repair rate arc demonstrated.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.2
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• pp.87-93
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• 2009

In this paper, we propose and evaluate the availability of single sensor node using a hierarchial modeling approach. We divides a sensor node into a software and hardware and analyze failures of each component. We construct Markov chains to represent the components of a sensor node, and then we construct a hierarchical model which use fault tree in upper level and Markov chains in lower level. We evaluate the availability and down of single sensor node.

• Proceedings of the Korean Society for Information Management Conference
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• 1998.08a
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• pp.97-100
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• 1998

계량정보학 연구영역의 하나인 운영연구(Operation Research, OR)중, 미래예측이라는 목적을 가지고 있는 마코프모형(Markov chains)의 통계기법을 활용한 두가지 실험사례를 살펴보고, 최근의 연구경향을 분석함으로써, 도서관 시스템 운영과 설계에 마코프모형을 응용할 수 있는 네가지 방안을 제시하였다. 계량정보학의 한분야로 적용되고 있는 마코프모형에 관한 국내연구가 활발하지 못한 상태이므로, 국내 계량정보학에서의 마코프모형 연구의 필요성과 활성화를 제안하였다.

• 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.

• Journal of Agricultural Extension & Community Development
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• v.24 no.1
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• pp.1-8
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• 2017

The Purpose of this study is to predict farm size per farming household in Chungcheongnam-province by using the Markov chains and Quadratic Programming.. The results are as follows; First, small-scale farms with less than 1.0ha of land are predicted to be still more than half (of total farming households) in 2025 as well. Second, large-scale farms with 3.0ha-5.0ha land and extra large-scale farms with over 5.0ha of land are predicted to gradually expand their proportion in total farm scale. Third, middle-scale farms with 1.0ha-3.0ha land are forecasted to be reduced in their relative proportion. It is required to take into account regional characteristics to improve the effectiveness of a rice industry policy. Therefore, this study has some significance in attempting to research on the ownership structure of rice production areas in consideration of target regions.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.31-42
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• 2015

The purpose of airborne radars is to detect and identify approaching targets as early as possible. If the targets are identified as enemies, detection systems must provide defense systems with information of the targets to counter. Though many previous studies based on the detection theory of the target have shown various ways to derive detection probability of each radar, optimal arrangement of radars for effective detection, and determination of the search pattern, they did not reflect the fact that most military radar sites run multiple radars in order to increase the accuracy of identifications by radars. In this paper, we propose a model to analyze the probability of identification generated by the multiple radars using non-homogeneous absorbing markov chains. Our results are expected to help the military commanders counter the enemy targets effectively by using radars in a way to maximize the identification rate of targets.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.263-275
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• 2014

The present study used a hierarchical Bayesian approach was used to develop a mixed effect model to describe the transitional behavior of subjects in time nonhomogeneous Markov chains. The posterior distributions of model parameters were not in analytically tractable forms; subsequently, a Gibbs sampling method was used to draw samples from full conditional posterior distributions. The proposed model was implemented with real data.

• Journal of the Korean Statistical Society
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• v.25 no.3
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• pp.303-311
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• 1996

We consider the discrete time randomly perturbed systems on sep-arable Banach space given by $X_{n+1};=;{Gamma}_{n+1}(X_n);+;{epsilon}_{n+1}$ where {${Gamma}_n$} is a sequence of random functions and {${epsilon}_n$} is a sequence of disturbances Sufficient conditions for non-ergodicity of {$X_n$} are obtained.

• Communications of the Korean Mathematical Society
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• v.11 no.1
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• pp.191-199
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• 1996

The strong shift equivalence of nonnegative integral square matrices is a necessary and sufficient condition for the topological conjugacy of topological Markov chains. In this paper we study the relation between strong shift equivalence and matrix conjugation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.514-514
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• 1994