• 대한전기학회논문지:전력기술부문A
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• 제55권12호
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• pp.536-543
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• 2006

This paper uses Monte Carlo technique, which is one of probabilistic methods of estimating the economical quantity of electric power generation in consideration of voltage stability in the aspect of power generation companies. In the power exchange system in Korea, when power generation companies participate in tenders for power generation capacity at the power exchange, they need to determine their power supply capacity considering the stability of electric power system. Thus, we purposed to propose an algorithm for estimating economical power generation capacity in theaspect of power generation companies, through which we can estimate the margin for voltage stability through P-V curve analysis by capacity according to the change of power generation capacity in a simulated system and to conduct Monte Carlo simulation in consideration of the margin

• Journal of Radiation Protection and Research
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• 제42권3호
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• pp.154-157
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• 2017

Background: Shielding properties of compound or mixture is presented in terms of mass attenuation coefficients using Monte Carlo simulation. Mass attenuation coefficients of cement, gypsum and the mixture of gypsum and $PbCO_3$ has been investigated using monte carlo MCNPX. Materials and Methods: The mass attenuation coefficients of cement, gypsum and the mixture of gypsum and $PbCO_3$ were calculated for photon energies 365.5, 661.6, 1,173.2, and 1,332.5 keV energies. Results and Discussion: The simulated values of mass attenuation coefficients were compared avaialable experimental results, theoretical values by XCOM and found good comparability of the results. Conclusion: Standard simulation geometry used in the present investigation would be very useful for various types of sample for shielding and dosimetry applications.

• 천문학논총
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• 제25권4호
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• pp.177-186
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• 2010

We developed an efficient Monte-Carlo algorithm to solve dust-scattering radiative transfer problems for continuum radiation. The method calculates the scattered intensities for various anisotropic factors ($g_i$) all at once, while actual photon packets are tracked following a scattering phase function given by a single anisotropic factor ($g_0$). The algorithm was tested by applying the method to a dust cloud embedding a star at the cloud center and found to provide accurate results within the statistical fluctuation that is intrinsic in Monte-Carlo simulations. It was found that adopting $g_0$ = 0.4 - 0.5 in the algorithm is most efficient. The method would be efficient in estimating the anisotropic factor of the interstellar dust by comparing the observed data with radiative transfer models.

• 대한전기학회논문지:전력기술부문A
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• 제52권1호
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• pp.9-16
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• 2003

In this paper, we propose a reliability evaluation method considering the momentary interruptions of power distribution systems. The results of research are concentrated on two parts. One is the analytic and probabilistic reliability evaluation of power distribution system considering the momentary interruptions and the other is the reliability cost evaluation that unifies the cost of sustained and momentary interruptions. This proposed reliability cost evaluation methodology is also divided into the analytic and probabilistic approach and the time sequential Monte Carlo method is used for the probabilistic method. The proposed methods are tested using the modified RBTS (Roy Billinton Test System) form and historical reliability data of KEPCO (Korea Electric Power Corporation) system. Through the case studies, it is verified that the proposed reliability evaluation and its cost/worth assessment methodologies can be applied to the actual reliability studies.

• Communications for Statistical Applications and Methods
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• 제31권1호
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• pp.65-85
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• 2024

The tail probability of a function of a multivariate random variable is not easy to estimate by the crude Monte Carlo simulation. When the occurrence of the function value over a threshold is rare, the accurate estimation of the corresponding probability requires a huge number of samples. When the explicit form of the cumulative distribution function of each component of the variable is known, the inverse transform likelihood ratio method is directly applicable scheme to estimate the tail probability efficiently. The method is a type of the importance sampling and its efficiency depends on the selection of the importance sampling distribution. When the cumulative distribution of the multivariate random variable is represented by a copula and its marginal distributions, we develop an iterative algorithm to find the optimal importance sampling distribution, and show the convergence of the algorithm. The performance of the proposed scheme is compared with the crude Monte Carlo simulation numerically.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 춘계 학술발표회 논문집
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• pp.67-72
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• 2002

A Bayesian testing procedure is proposed for assessment of bioequivalence in both mean and variance which ensures population bioequivalence under normality assumption. We derive the joint posterior distribution of the means and variances in a standard 2 ${\times}$ 2 crossover experimental design and propose a Bayesian testing procedure for bioequivalence based on a Markov chain Monte Carlo methods. The proposed method is applied to a real data set.

• 한국CDE학회논문집
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• 제2권4호
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• pp.215-221
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• 1997

A new approach in solving design centering problem is presented. Like most stochastic optimization problems, optimal design centering problems have intrinsic difficulties in multivariate intergration of probability density functions. In order to avoid to avoid those difficulties, genetic algorithm and very coarse Monte Carlo simulation are used in this research. The new algorithm performs robustly while producing improved yields. This result implies that the combination of robust optimization methods and approximated simulation schemes would give promising ways for many stochastic optimizations which are inappropriate for mathematical programming.

• 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.

• Communications for Statistical Applications and Methods
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• 제4권2호
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• pp.523-532
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• 1997

We propose several estimators of the reliability function R of the two-parameter exponential distribution, and then compare those estimator in terms of the mean square error (MSE) through Monte Carlo method. We also consider the parametric bootstrap estimation. Using the parametric bootstrap estimator, we obtain the bootstrap confidence intervals for reliability function and compare the proposed bootstrap confidence intervals in terms of the length and the coverage probability through Monte Carlo method.

• Communications for Statistical Applications and Methods
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• 제22권1호
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• pp.81-93
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• 2015

Validity of the stationary bootstrap of Politis and Romano (1994) is proved for U-statistics under strong mixing. Weak and strong consistencies are established for the stationary bootstrap of U-statistics. The theory is applied to a symmetry test which is a U-statistic regarding a kernel density estimator. The theory enables the bootstrap confidence intervals of the means of the U-statistics. A Monte-Carlo experiment for bootstrap confidence intervals confirms the asymptotic theory.