• Management Science and Financial Engineering
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• 제13권1호
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• pp.35-53
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• 2007

We consider a(worst-case) robust optimization version of the Economic Order Quantity(EOQ) model. Order setup costs and inventory carrying costs are assumed to have uncertainty in their values, and the uncertainty description of the two parameters is supposed to be given by an ellipsoidal representation. A genetic algorithm combined with Monte Carlo simulation is proposed to approximate the ellipsoidal representation. The objective function of the model under ellipsoidal uncertainty description is derived, and the resulting problem is solved by another genetic algorithm. Computational test results are presented to show the performance of the proposed method.

• 한국응용과학기술학회지
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• 제34권1호
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• pp.125-131
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• 2017

콘크리트 혼화제의 무수축 그라우트에서 산란체와 흡수체의 영향은 빛산란에 의해 파장에 대한 산란세기로 설명된다. New Austria Tunnel Method의 수지에 대한 산란의 분자특성들은 연구하기 위해 Monte Carlo Simulation하였다. 이는 산란매질에서 광학적 파라미터들(${\mu}_s$, ${\mu}_a$, ${\mu}_t$)에 의해 조사되어 그들의 영향을 알 수 있었다. 산란매질에서 광자에 대한 빛 분포에 의한 결과는 광원에서 검출기까지 거리가 가까우면 무수축혼화제의 산란이 증가하여 산란세기가 크게 나타나는데 혼화제가 첨가함에 따라 무수축 성질이 크게 나타났다. 이는 강구조물의 내구성을 위한 코팅과 부식에서 좋은 모델을 디자인하는데 도움이 될 것이다.

• 한국응용과학기술학회지
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• 제29권3호
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• pp.473-479
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• 2012

혼탁매질에서 산란체와 흡수체의 영향은 빛산란에 의해 파장에 대한 산란세기로 설명된다. New Austria Tunnel Method의 수지에 대한 산란의 분자특성들은 연구하기 위해 Monte Carlo Simulation하였다. 이는 산란매질에서 광학적 파라미터들(${\mu}_s$, ${\mu}_a$, ${\mu}_t$)에 의해 조사되어 그들의 영향을 알 수 있었다. 산란매질에서 광자에 대한 빛분포에 의한 결과는 광원에서 검출기까지 거리가 가까우면 산란이 증가하여 산란세기가 크게 나타났다. 이는 강구조물의 내구성을 위한 코팅과 부식에서 좋은 모델을 디자인하는데 도움이 될 것이다.

• 한국물환경학회지
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• 제36권5호
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• pp.373-384
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• 2020

Hydrological models are based on a combination of parameters that describe the hydrological characteristics and processes within a watershed. For this reason, the model performance and accuracy are highly dependent on the parameters. However, model uncertainties caused by parameters with stochastic characteristics need to be considered. As a follow-up to the study conducted by Choi et al (2020), who developed a relatively simple semi-distributed hydrological model, we propose a tool to estimate the posterior distribution of model parameters using the Metropolis-Hastings algorithm, a type of Markov-Chain Monte Carlo technique, and analyze the uncertainty of model parameters and simulated stream flow. In addition, the uncertainty caused by the parameters of each version is investigated using the lumped and semi-distributed versions of the applied model to the Hapcheon Dam watershed. The results suggest that the uncertainty of the semi-distributed model parameters was relatively higher than that of the lumped model parameters because the spatial variability of input data such as geomorphological and hydrometeorological parameters was inherent to the posterior distribution of the semi-distributed model parameters. Meanwhile, no significant difference existed between the two models in terms of uncertainty of the simulation outputs. The statistical goodness of fit of the simulated stream flows against the observed stream flows showed satisfactory reliability in both the semi-distributed and the lumped models, but the seasonality of the stream flow was reproduced relatively better by the distributed model.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.268-275
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• 2003

We consider the Bayesian accelerated failure time model. The error distribution is assigned a skewed normal distribution which is including normal distribution. For noninformative priors of regression coefficients, we show the propriety of posterior distribution. A Markov Chain Monte Carlo algorithm(i.e., Gibbs Sampler) is used to obtain a predictive distribution for a future observation and Bayes estimates of regression coefficients.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 춘계 학술발표회 논문집
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• pp.183-189
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• 2003

A momentum threshold autoregressive (MTAR) model, a nonlinear autoregressive model, is analyzed in a Bayesian framework. Parameter estimation in the presence of missing data is done by using Markov chain Monte Carlo methods. We also propose simple Bayesian test procedures for asymmetry and unit roots. The proposed method is applied to a set of Korea unemployment rate data and reveals evidence for asymmetry and a unit root.

• 대한기계학회논문집A
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• 제24권12호
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• pp.2917-2925
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• 2000

Tensile strength and failure process of composite materials depend on the variation in fiber strength, matrix properties and fiber-matrix interfacial shear strength. A Monte-Carlo simulation considering variation in these factors has been widely used to analyze such a complicated phenomenon as a strength and simulated the failure process of unidirectional composites. In this study, a Monte Carlo simulation using 2-D and 3-D(square and hexagonal array) model was performed on unidirectional graphite/epoxy and glass/polyester composites. The results simulated by using 3-D hexagonal array model have a good agreement with the experimental data which were tensile strength and failure process of unidirectional composites.

• Journal of Magnetics
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• 제20권1호
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• pp.11-20
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• 2015

In this work, Monte Carlo simulation was employed to model the stretchable Ising monolayer film to investigate the effect of the spatial distance variation among magnetic atoms on magnetic behavior of the film. The exchange interaction was considered as functions of initial interatomic distance and the stretched distance (or the strain). Following Bethe-Slater picture, the magnetic exchange interaction took the Lennard-Jones potential-like function. Monte Carlo simulations via the Wolff and Metropolis algorithms were used to update the spin systems, where equilibrium and dynamic magnetic profiles were collected. From the results, the strain was found to have strong influences on magnetic behavior, especially the critical behavior. Specifically, the phase transition point was found to either increase or decrease depending on how the exchange interaction shifts (i.e. towards or away from the maximum value). In addition, empirical functions which predict how the critical temperatures scale with initial interatomic distance and the strain were proposed, which provides qualitatively view how to fine tune the magnetic critical point in monolayer film using the substrate modification induced strain.

• 한국물환경학회지
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• 제36권5호
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• pp.353-363
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• 2020

Hydrologic models can be classified into two types: those for understanding physical processes and those for predicting hydrologic quantities. This study deals with how to use the model to predict today's stream flow based on the system's knowledge of yesterday's state and the model parameters. In this regard, for the model to generate accurate predictions, the uncertainty of the parameters and appropriate estimates of the state variables are required. In this study, a relatively simple hydrologic partitioning model is proposed that can explicitly implement the hydrologic partitioning process, and the posterior distribution of the parameters of the proposed model is estimated using the Markov chain Monte Carlo approach. Further, the application method of the ensemble Kalman filter is proposed for updating the normalized soil moisture, which is the state variable of the model, by linking the information on the posterior distribution of the parameters and by assimilating the observed steam flow data. The stochastically and recursively estimated stream flows using the data assimilation technique revealed better representation of the observed data than the stream flows predicted using the deterministic model. Therefore, the ensemble Kalman filter in conjunction with the Markov chain Monte Carlo approach could be a reliable and effective method for forecasting daily stream flow, and it could also be a suitable method for routinely updating and monitoring the watershed-averaged soil moisture.

• 한국물환경학회지
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• 제24권2호
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• pp.239-246
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• 2008

In this study, an optimized deterministic water-quality model was constructed to estimate water quality of a river and lake in the upstream basin of a dam. A stochastic water-quality analysis using reliability analysis technique was applied to the model. The model was tested in the 13.9 km reach from Maeil stage station of Kyechun to Hoengsung Dam of Sum River. After finding hydraulic characteristics from nonuniform flow analysis, Broyden-Fletcher-Goldfarb-Shanno (BFGS) optimization technique for model calibration was applied to determine optimum reaction parameters, and model verification was performed based on these. The stochastic model, using Mean First­Order Second­-Moment (MFOSM) and Monte-Carlo methods, was applied to the same reach as the deterministic study. Variations of discharge and water quality in headwater were considered, as well as variations of hydraulic coefficients and reaction coefficients. The statistical results of output variables from MFOSM were similar to those from the Monte-Carlo method. Risk analysis using MFOSM and Monte-Carlo methods presented the probabilities of some locations in the Hoengsung Lake violating existing water-quality standards in terms of DO and BOD.