• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.864-867
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• 2012

사람들이 휴대용 위치정보 수집 장비나 혹은 스마트폰을 사용하면서 사람의 이동 정보인 위치정보들을 모으는 일이 가능해 졌다. 이러한 위치정보들을 가지고 본 논문에서는 사람의 이동 모델을 나타내고자 하였다. 이동 정보들은 머물러 있는(Stay)상태와 이동하는(Moving) 상태로 나눌 수 있는데 이러한 상태 중 머물러 있는 상태가 군집화가 되어 연쇄 모델속의 하나의 상태(State)로 나타나 질 수 있다. 물론 이동 정보들을 통해 연쇄모델 속 각 상태간의 전이 확률 또한 계산 할 수 있다. 이러한 일련의 과정을 본 논문에서는 기대치 최대화 기반 군집화 과정을 통해 연속시간 연쇄 모델의 형태로 인간의 이동성을 표현하였다. 또한 이러한 모델에서 대표 군집(macro)과 그 부속 군집(micro)을 표현할 수 있었고 이러한 모습은 대표적인 큰 군집 속의 작은 군집의 형태로 나타나게 된다.

• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.99-110
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• 2000

In this study we proposed a simple method for generating multi-site daily rainfall based on the 1-order Markov chain and considering the spatial correlation. The occurrence of rainfall is simulated by a simple 1st-order Markov chain and its intensity to be chosen randomly from the observed data. The spatial correlation between sites could be conserved as the rainfall intensity at each site is to be chosen consistently with the target site in time through generation. It is found that the generated daily rainfall data reproduce genera] characteristics of the observed data such as average, standard deviation, average number of wet and dry days, but the clustering level in time is somewhat loosened. Thus, the lag-I correlation coefficient of the generated data gave smaller value than the observed, also the average lengths of wet run and dry run and the wet-to-wet and dry-to-dry probabilities were a bit less than the observed. This drawback seems to be overcome somewhat by choosing a proper site representing overall basin characteristics or by use of more detailed states of rainfall occurrence.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.619-629
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• 2002

Water in the atmosphere is circulated by reciprocal action of various factors in the climate system. Otherwise, any climate phenomenon could not occur of itself. Thus, we have tried to understand the climate change by analysis of the factors. In this study, the fuzzy theory which is useful to express inaccurate and approximate nature in the real world is used for forecasting precipitation influenced by the factors. Forecasting models used in this study are neuro-fuzzy system and a Markov chain and those are applied to precipitation forecasting of illinois. Various atmosphere circulation factors(like soil moisture and temperature) influencing the climate change are considered to forecast precipitation. As a forecasting result, it can be found that the considerations of the factors are helpful to increase the forecastibility of the models and the neuro-fuzzy system gives us relatively more accurate forecasts.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.317-320
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• 2022

This paper studies real-time error in the context of monitoring a symmetric binary information source over a delay system. To obtain the average real-time error, the delay system is modeled and analyzed as a discrete time Markov chain with a finite state space. Numerical analysis is performed on various system parameters such as state transition probabilities of information source, transmission times, and transmission frequencies. Given state transition probabilities and transmission times, we investigate the relationship between the transmission frequency and the average real-time error. The results can be used to investigate the relationship between real-time errors and age of information.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.1-12
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• 2017

Many stochastic processes satisfy the Markov property exactly or at least approximately. An interested property in the Markov process is the first passage time. Since the sequential analysis by Wald, the approximation of the first passage time has been studied extensively. The Statistical computing technique due to the development of high-speed computers made it possible to calculate the values of the properties close to the true ones. This article introduces an exponentially weighted moving average (EWMA) control chart as an example of the Markov process, and studied how to calculate the average run length with problematic issues that should be cautioned for correct calculation. The results derived for approximation of the first passage time in this research can be applied to any of the Markov processes. Especially the approximation of the continuous time Markov process to the discrete time Markov chain is useful for the studies of the properties of the stochastic process and makes computational approaches easy.

• Journal of the Society of Naval Architects of Korea
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• v.36 no.4
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• pp.137-146
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• 1999

Inspection becomes to be important in the safety of structure and economical viewpoint, because structural damage accompanies lots of economical cost and social problems. Especially ship structure is composed of a lot of members and it is impossible to inspect all members continuously. The purpose of this paper is to get optimal inspection plan containing inspection time and method. Crack is one of major modes on the structural failure and can lead to collapse of structure. In this paper, the deteriorating process, which contains inspection to detect the crack before the propagation to large crack, is idealized as Markov chain model. Genetic algorithm is also used to accomplish the optimization of inspection plan. Especially, the probabilistic characteristics of cracks are changed, because ship is operating in corrosive environments and the scantling of structural members is reduced due to corrosion. Non-stationary Markov chain model is used to represent the process of corrosion in structural members. In this paper, the characteristics of indivisual inspection plan are compared by numerical examples for the change of corrosion rate, the cost due to scheduled system down and target failure probability. From the numerical example, it can be seen that the improvement of fatigue life for the members with short fatigue life is the most effective way in order to reduce total maintenance cost.

• Journal of Korea Water Resources Association
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• v.37 no.4
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• pp.305-314
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• 2004

Climate change mainly due to the increase of green house gases cause different patterns of water cycle within the basin. However, it is common that current planning and management practices do not consider the effect of the climate change. So, this study evaluated the effect of climate change on the water circulation within the watershed. This study used several GCM simulations for the double $CO_2$condition for the generation of temperature and rainfall series using the Markov chain. Daily runoff series for 100 years were generated using a rainfall-runoff model. As results. annual temperature increase by ＋3.2 ∼＋4.6$^{\circ}C$, annual precipitation change －7 ∼ ＋8 %, annual runoff change －14 ∼ ＋7 %, and potential evapotranspiration amount change ＋3 ∼＋4 % for the change of 1 $^{\circ}C$ are found to be expected depending on GCM simulations. Even though the simulation results are very dependent on the GCM predictions considered, overall variability of runoff is expected to become higher than the current state.

• Journal of KIISE
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• v.42 no.6
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• pp.748-754
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• 2015

This paper proposes a sequential state estimation model consisting of continuous and discrete variables, as a way of generalizing all discrete-state factorial HMM, and gives a design of gait motion model based on the idea. The discrete state variable implements a Markov chain that models the gait dynamics, and for each state of the Markov chain, we created a Gaussian process over the space of the continuous variable. The Markov chain controls the switching among Gaussian processes, each of which models the rotation or various views of a gait state. Then a particle filter-based algorithm is presented to give an approximate filtering solution. Given an input vector sequence presented over time, this finds a trajectory that follows a Gaussian process and occasionally switches to another dynamically. Experimental results show that the proposed model can provide a very intuitive interpretation of video-based gait into a sequence of poses and a sequence of posture states.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.203-211
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• 2023

A Markov chain Monte Carlo (MCMC) simulation is proposed for probabilistic full waveform inversion (FWI) in a layered half-space. Dynamic responses on the half-space surface are estimated using the thin-layer method when a harmonic vertical force is applied. Subsequently, a posterior probability distribution function and the corresponding objective function are formulated to minimize the difference between estimations and observed data as well as that of model parameters from prior information. Based on the gradient of the objective function, a proposal distribution and an acceptance probability for MCMC samples are proposed. The proposed MCMC simulation is applied to several layered half-space examples. It is demonstrated that the proposed MCMC simulation for probabilistic FWI can estimate probabilistic material properties such as the shear-wave velocities of a layered half-space.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.4
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• pp.1241-1250
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• 1996

The characteristics of fatigue cumulative damage and fatigue life of 8-harness satin woven CFRP composites with a circular hole under constant amplitude and 2-level block loading are estimated by Stochastic Makov chain model. It is found in this study that the fatigue damage accumulation behavior is very random and the fatigue damage is accumulated as two regions under constant amplitude fatigue loading. In constant amplitude fatigue loading the predicted mean number of cycles to a specified damage state by Markov chain model shows a good agreement with the test result. The predicted distribution of the fatigue cumulative damage by Markov chain model is similar to the test result. The fatigue life predictions under 2-level block loading by Markov chain model revised are good fitted to the test result more than by 2-parameter Weibull distribution function using percent failure rule.