• Title/Summary/Keyword: 마코프 모형

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Probabilistic Assessment of Hydrological Drought Using Hidden Markov Model in Han River Basin (은닉 마코프 모형을 이용한 한강유역 수문학적 가뭄의 확률론적 평가)

  • Park, Yei Jun;Yoo, Ji Young;Kwon, Hyun-Han;Kim, Tae-Woong
    • Journal of Korea Water Resources Association
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    • v.47 no.5
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    • pp.435-446
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    • 2014
  • Various drought indices developed from previous studies can not consider the inherent uncertainty of drought because they assess droughts using a pre-defined threshold. In this study, to consider inherent uncertainty embedded in monthly streamflow data, Hidden Markov Model (HMM) based drought index (HMDI) was proposed and then probabilistic assessment of hydrologic drought was performed using HMDI instead of using pre-defined threshold. Using monthly streamflow data (1966~2009) of Pyeongchang river and Upper Namhan river provided by Water Management Information System (WAMIS), applying the HMM after moving-averaging the data with 3, 6, 12 month windows, this study calculated the posterior probability of hidden state that becomes the HMDI. For verifying the method, this study compared the HMDI and Standardized Streamflow Index (SSI) which is one of drought indices using a pre-defined threshold. When using the SSI, only one value can be used as a criterion to determine the drought severity. However, the HMDI can classify the drought condition considering inherent uncertainty in observations and show the probability of each drought condition at a particular point in time. In addition, the comparison results based on actual drought events occurred near the basin indicated that the HMDI outperformed the SSI to represent the drought events.

A nonparametric Bayesian seemingly unrelated regression model (비모수 베이지안 겉보기 무관 회귀모형)

  • Jo, Seongil;Seok, Inhae;Choi, Taeryon
    • The Korean Journal of Applied Statistics
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    • v.29 no.4
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    • pp.627-641
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    • 2016
  • In this paper, we consider a seemingly unrelated regression (SUR) model and propose a nonparametric Bayesian approach to SUR with a Dirichlet process mixture of normals for modeling an unknown error distribution. Posterior distributions are derived based on the proposed model, and the posterior inference is performed via Markov chain Monte Carlo methods based on the collapsed Gibbs sampler of a Dirichlet process mixture model. We present a simulation study to assess the performance of the model. We also apply the model to precipitation data over South Korea.

Stochastic analysis of a two-unit parallel system with three types of failure & preventive maintenance (예방보수와 3가지 형태의 고장을 갖는 두 요소로 구성된 병렬 시스템의 확률분석)

  • Che-Soong Kim
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.16 no.27
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    • pp.11-19
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    • 1993
  • 본 논문에서는 여러 가지 형태의 고장을 갖는 동일한 두 요소로 구성된 병렬 시스템의 신뢰도를 평가하는 마코프 모형을 제시하였다. 여기서 고려하는 고장형태는 인간의 오류에 의한 고장, 하드웨어에 의한 고장, 하나의 원인에 의해서 여러개의 구성요소가 동시에 고장나는 Common cause 고장형태로 나누었다. 시스템은 임의의 시점에서 예방보수를 받을수 있고, 고장률과 예방 보수률은 일정하다고 가정했다. 또한 수리률이 임의의 분포를 따를 경우 시스템 신뢰도 및 평균 고장시간을 구했다.

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A Bayesian Prediction of the Generalized Pareto Model (일반화 파레토 모형에서의 베이지안 예측)

  • Huh, Pan;Sohn, Joong Kweon
    • The Korean Journal of Applied Statistics
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    • v.27 no.6
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    • pp.1069-1076
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    • 2014
  • Rainfall weather patterns have changed due to global warming and sudden heavy rainfalls have become more frequent. Economic loss due to heavy rainfall has increased. We study the generalized Pareto distribution for modelling rainfall in Seoul based on data from 1973 to 2008. We use several priors including Jeffrey's noninformative prior and Gibbs sampling method to derive Bayesian posterior predictive distributions. The probability of heavy rainfall has increased over the last ten years based on estimated posterior predictive distribution.

An EM Algorithm-Based Approach for Imputation of Pixel Values in Color Image (색조영상에서 랜덤결측화소값 대체를 위한 EM 알고리즘 기반 기법)

  • Kim, Seung-Gu
    • The Korean Journal of Applied Statistics
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    • v.23 no.2
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    • pp.305-315
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    • 2010
  • In this paper, a frequentistic approach to impute the values of R, G, B-components in random missing pixels of color image is provided. Under assumption that the given image is a realization of Gaussian Markov random field, its model is designed such that each neighbor pixel values for a given pixel follows (independently) the normal distribution with covariance matrix scaled by an evaluates of the similarity between two pixel values, so that the imputation is not to be affected by the neighbors with different color. An approximate EM-based algorithm maximizing the underlying likelihood is implemented to estimate the parameters and to impute the missing pixel values. Some experiments are presented to show its effectiveness through performance comparison with a popular interpolation method.

Fast Text Line Segmentation Model Based on DCT for Color Image (컬러 영상 위에서 DCT 기반의 빠른 문자 열 구간 분리 모델)

  • Shin, Hyun-Kyung
    • The KIPS Transactions:PartD
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    • v.17D no.6
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    • pp.463-470
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    • 2010
  • We presented a very fast and robust method of text line segmentation based on the DCT blocks of color image without decompression and binary transformation processes. Using DC and another three primary AC coefficients from block DCT we created a gray-scale image having reduced size by 8x8. In order to detect and locate white strips between text lines we analyzed horizontal and vertical projection profiles of the image and we applied a direct markov model to recover the missing white strips by estimating hidden periodicity. We presented performance results. The results showed that our method was 40 - 100 times faster than traditional method.

A redistribution model for spatially dependent Parrondo games (공간의존 파론도 게임의 재분배 모형)

  • Lee, Jiyeon
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.1
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    • pp.121-130
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    • 2016
  • An ansemble of N players arranged in a circle play a spatially dependent Parrondo game B. One player is randomly selected to play game B, which is based on the toss of a biased coin, with the amount of the bias depending on states of the selected player's two nearest neighbors. The player wins one unit with heads and loses one unit with tails. In game A' the randomly chosen player transfers one unit of capital to another player who is randomly chosen among N - 1 players. Game A' is fair with respect to the ensemble's total profit. The games are said to exhibit the Parrondo effect if game B is losing and the random mixture game C is winning and the reverse-Parrondo effect if game B is winning and the random mixture game C is losing. We compute the exact mean profits for games B and C by applying a state space reduction method with lumped Markov chains and we sketch the Parrondo and reverse-Parrondo regions for $3{\leq}N{\leq}6$.

ATM교환 시스팀의 최적설계를 위한 확률 모형

  • 김제승;윤복식;이창훈
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1992.04b
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    • pp.457-465
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    • 1992
  • 현재 또는 장래에 예견되는 거의 모든 통신서비스를 통합적으로 제공할 수 있는 B-ISDN환경하에서 음성통화와 비디오정보, 데이타들이 각기 다른 bit rate와 서비스 요구조건(통화시간, 질등)를 가지고 전송서비스를 받으려 하기때문에 매우 다양한 서비스들의 조합을 고려하여 교환시스팀을 구현해야 한다. B-ISDN에 적합한 전송기술로서 ATM(Asynchronous Transfer Mode)이 일반적으로 제안되고 있는데 이미 10여종의 독특한 ATM시스팀들이 이론적, 실험적 연구단계를 거쳐 거의 실용화 단계까지 이르렀다고 주장되고 있다. 본 논문에서는 ATM교환시스팀의 설계요건과 비교기준을 제시하여 설계 대자인을 주어진 기술제약하에 최적화 할 수 있는 조건을 제시한다. 이때 우선 기본 스위치의 구조를 단단계로 할 것인가 다단계로 할 것인가에 대한 정량적, 확률적인 비교가 행해지고 특히 이미 많은 ATM스위치에서 채택되고 있는 Banyan형태의 망의 성능분석을 보다 현실에 근접하게 할 수 있는 이산적 마코프체인에 의한 모형과 계산방법이 확립된다. 이를 통해 단위스위치내부에 버퍼의 유무, 버퍼를 두는 위치, 또한 버퍼사이즈에 의한 영향등이 세부적으로 분석된다.

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EM Algorithm-based Segmentation of Magnetic Resonance Image Corrupted by Bias Field (바이어스필드에 의해 왜곡된 MRI 영상자료분할을 위한 EM 알고리즘 기반 접근법)

  • 김승구
    • The Korean Journal of Applied Statistics
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    • v.16 no.2
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    • pp.305-319
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    • 2003
  • This paper provides a non-Bayesian method based on the expanded EM algorithm for segmenting the magnetic resonance images degraded by bias field. For the images with the intensity as a pixel value, many segmentation methods often fail to segment it because of the bias field(with low frequency) as well as noise(with high frequency). Our contextual approach is appropriately designed by using normal mixture model incorporated with Markov random field for noise-corrective segmentation and by using the penalized likelihood to estimate bias field for efficient bias filed-correction.

BMAP/PH/N Queueing Model with Retrial and Losses (재시도와 손실을 고려한 BMAP/PH/N 대기모형 분석)

  • Kim, Che-Soong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.29 no.1
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    • pp.41-46
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    • 2006
  • 본 논문에서는 재시도와 완전입력 규칙을 갖는 BMAP/PH/N/0 대기시스템에 대한 주요 성능평가척도와 시스템의 정상상태 조건을 제시한다. 고려되는 시스템은 모든 서버가 서비스를 하고 있을 경우 도착이 이루어지는 배치도착은 모두 손실되며, 반대의 경우 도착하는 배치는 서비스를 받기 위해 시스템에 들어가게 된다. 만약 쉬고 있는 서버의 수가 불충분하여 배치의 일부가 즉각 서비스를 받을 수 없다면, 일단 오빗으로 이동하고 표준 재시도 대기 시스템의 규칙에 따라 후에 서비스를 받게 된다. 본 논문에서는 배치 마코프도착과정, 단계 서비스분포 및 유한버퍼를 갖는 다중서버 재시도 대기 시스템에 대한 수리모형을 제시한다. 제시된 시스템의 정상상태 분포 존재를 위한 충분조건을 유도하고, 이 분포를 계산하기 위한 알고리즘이 제시된다. 끝으로 완전입력규칙을 갖는 시스템에 대한 손실확률을 계산하기 위한 식이 유도하고, 수치 예제들을 제시한다.