• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2015년도 학술발표회
• /
• pp.225-225
• /
• 2015

Drought events usually evolve slowly in time and their impacts generally span a long period of time. This indicates that the sequence of drought is not completely random. The Hidden Markov Model (HMM) is a probabilistic model used to represent dependences between invisible hidden states which finally result in observations. Drought characteristics are dependent on the underlying generating mechanism, which can be well modelled by the HMM. This study employed a HMM with Gaussian emissions to fit the Standardized Precipitation Index (SPI) series and make multi-step prediction to check the drought characteristics in the future. To estimate the parameters of the HMM, we employed a Bayesian model computed via Markov Chain Monte Carlo (MCMC). Since the true number of hidden states is unknown, we fit the model with varying number of hidden states and used reversible jump to allow for transdimensional moves between models with different numbers of states. We applied the HMM to several stations SPI data in South Korea. The monthly SPI data from January 1973 to December 2012 was divided into two parts, the first 30-year SPI data (January 1973 to December 2002) was used for model calibration and the last 10-year SPI data (January 2003 to December 2012) for model validation. All the SPI data was preprocessed through the wavelet denoising and applied as the visible output in the HMM. Different lead time (T= 1, 3, 6, 12 months) forecasting performances were compared with conventional forecasting techniques (e.g., ANN and ARMA). Based on statistical evaluation performance, the HMM exhibited significant preferable results compared to conventional models with much larger forecasting skill score (about 0.3-0.6) and lower Root Mean Square Error (RMSE) values (about 0.5-0.9).

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2016년도 학술발표회
• /
• pp.197-197
• /
• 2016

Forecasting future drought events in a region plays a major role in water management and risk assessment of drought occurrences. The creeping characteristics of drought make it possible to mitigate drought's effects with accurate forecasting models. Drought forecasts are inevitably plagued by uncertainties, making it necessary to derive forecasts in a probabilistic framework. In this study, a new probabilistic scheme is proposed to forecast droughts, in which a discrete-time finite state-space hidden Markov model (HMM) is used aggregated with the Representative Concentration Pathway 8.5 (RCP) precipitation projection (HMM-RCP). The 3-month standardized precipitation index (SPI) is employed to assess the drought severity over the selected five stations in South Kore. A reversible jump Markov chain Monte Carlo algorithm is used for inference on the model parameters which includes several hidden states and the state specific parameters. We perform an RCP precipitation projection transformed SPI (RCP-SPI) weight-corrected post-processing for the HMM-based drought forecasting to derive a probabilistic forecast that considers uncertainties. Results showed that the HMM-RCP forecast mean values, as measured by forecasting skill scores, are much more accurate than those from conventional models and a climatology reference model at various lead times over the study sites. In addition, the probabilistic forecast verification technique, which includes the ranked probability skill score and the relative operating characteristic, is performed on the proposed model to check the performance. It is found that the HMM-RCP provides a probabilistic forecast with satisfactory evaluation for different drought severity categories, even with a long lead time. The overall results indicate that the proposed HMM-RCP shows a powerful skill for probabilistic drought forecasting.

• 디지털융복합연구
• /
• 제19권2호
• /
• pp.61-69
• /
• 2021

평균 수명과 연금 선택률 증가에 따른 군인연금 적자가 늘어나고 있으며 이에 대한 중요한 원인은 군인연금 수령자의 지속적인 증가로 추정되고 있다. 군인연금 재정의 건전성 측면에서 중·장기적인 군인연금 수령자의 규모를 확인하는 연구가 부족한 현실에서 본 연구는 마코프 체인 모형을 이용하여 군인집단의 안정상태를 확인하여 재직 인원대비 연금수령 비율인 부양률 측면에서 향후 군인연금 제도가 나아가야 할 방향을 제시하고 검증을 통해 적용 방법의 타당성을 확인한다. 본 연구를 통해서 초기 45,270 명 수준의 군 재직 인원은 일정 시간이 지나면 43,141 명으로 수렴하여 안정상태에 도달하는 것을 확인하였으며 이를 통해 군인연금 수령자의 중·장기적 규모를 추정하여 부양률 측면에서 국가 재정지원의 방향성을 확인할 수 있을 것으로 기대된다. 군인연금 수령자 대상인 20년 이상의 군인은 다른 민간직업과 비교하여 이직 또는 퇴직하는 비율이 상대적으로 낮은 상태로 상태 정의가 수월하고 상태에 대한 전이확률을 단순하게 적용할 수 있다. 따라서 군인집단을 하나의 시스템으로 보고 그 활동기간 중 진급, 현 계급 유지, 퇴직 등의 상태 전이확률을 확인하여 마코프 체인 모형에 적용함으로써 안정적 상태의 군인집단 상태를 도출하여 장기적 관점에서 군인연금의 지속가능성을 확인할 수 있을 것으로 기대한다.

• Journal of information and communication convergence engineering
• /
• 제5권2호
• /
• pp.88-92
• /
• 2007

In this paper, an SS-RRA protocol that is based on Code Division Multiple Access is proposed and analyzed under the integrated voice and data traffic load. The backward logical channels consist of slotted time division frames with multiple spreading codes per slot. The protocol uses a reservation mechanism for the voice traffic, and a random access scheme for the data traffic. A discrete-time, discrete-state Markov chain is used to evaluate the performance. The numerical results show that the performance can be significantly improved by a few distinct spreading codes.

• 한국국방경영분석학회지
• /
• 제6권2호
• /
• pp.151-184
• /
• 1980

Simple models for a defense consisting of a preinstalled mine field possibly defended by an anti-tank weapon are derived and analyzed. This paper uses a special Poisson process to model the one or two positions of mines in the mine field. The duel between the anti-tank weapon and offensive tanks crossing the field is modeled with a continuous time Markov chain. Some algebraic solutions and numerical results are obtained for specific scenarios.

• Journal of applied mathematics & informatics
• /
• 제31권1_2호
• /
• pp.241-246
• /
• 2013

Choi [1] identified and characterized the limiting diffusion of this diploid model by defining discrete generator for the rescaled Markov chain. In this note, we define the operator of projection $S_t$ on limiting diffusion and new measure $dQ=S_tdP$. We show the martingale property on this operator and measure. Also we conclude that the martingale problem for diffusion operator of projection is well-posed.

• ETRI Journal
• /
• 제25권1호
• /
• pp.55-58
• /
• 2003

We propose a new paging strategy to reduce paging cost by adding paging agents at base stations. When a mobile-terminated call occurs, the base stations look up the paging agents to determine if terminal paging is actually to be made. An analytical model based on a Markov chain is used to evaluate the performance of the proposed strategy. The numerical results show that the proposed strategy significantly reduces the paging cost compared with the simultaneous paging strategy.

• Journal of the Korean Statistical Society
• /
• 제36권2호
• /
• pp.183-200
• /
• 2007

We consider a nonlinear autoregressive moving average model with nonlinear GARCH errors, and find sufficient conditions for the existence of a strictly stationary solution of three related time series equations. We also consider a geometric ergodicity and functional central limit theorem for a nonlinear autoregressive model with nonlinear ARCH errors. The given model includes broad classes of nonlinear models. New results are obtained, and known results are shown to emerge as special cases.

• 응용통계연구
• /
• 제14권2호
• /
• pp.379-391
• /
• 2001

본 연구에서는 관심거리가 되고 있는 마코프인쇄 몬테칼로(Markov Chain Monte Carlo, MCMC)방법에 근거한 공간 확률난수 (spatial random variate)생성법과 깁스표본추출법(Gibbs sampling)에 의한 베이지안 분석 방법에 대한 기술적 사항들에 관하여 검토하였다. 먼저 기본적인 확률난수 생성법과 관련된 사항을 살펴보고, 다음으로 조건부명시법(conditional specification)을 이용한 공간 확률난수 생성법을 예를 들어 살펴보기로한다. 다음으로는 이렇게 생성된 공간자료를 분석하기 위하여 깁스표본추출법을 이용한 베이지안 사후분포를 구하는 방법을 살펴보았다.

• Journal of the Korean Data and Information Science Society
• /
• 제13권2호
• /
• pp.227-234
• /
• 2002

In this paper, we consider hierarchical Bayes generalized linear models for the analysis of longitudinal count data. Specifically we introduce the hierarchical Bayes random effects models. We discuss implementation of the Bayes procedures via Markov chain Monte Carlo (MCMC) integration techniques. The hierarchical Baye method is illustrated with a real dataset and is compared with other statistical methods.