• 한국공작기계학회논문집
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• 제17권1호
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• pp.71-76
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• 2008

Nonlinear dynamic system under random excitation was analyzed by using stochastic method. A linearization method was used in order to linearize non-linear structural characteristics but the parametric excitation was used as it was given. An equivalent energy method which equalizes the expectation value of energy of the original nonlinear system and that of quasi-linearized system was proposed. Ito's differential rule was applied to obtain steady state moments. Quasi-linearization coefficients can be obtained the iterative calculation of linearization scheme and steady state moments. Monte Carlo simulation was used to verify the results of the proposed method. Nonlinear vibration of a slender beam was analyzed in this research. The analysis results were compared with Monte Carlo simulation result and showed good agreement. As the spectral density of the given excitation increased, the analysis results showed the better agreement with Monte Carlo simulation.

• 한국전자파학회논문지
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• 제17권1호
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• pp.39-44
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• 2006

본 논문에서는 바다 표면에서 전파의 페이딩 현상을 해석하는데 필요한 bistatic coherent reflectivity를 Monte-Carlo/모멘트 법과 physical optics(PO) 모델을 이용하여 비교하고 계산하였다. 모멘트 법 계산을 위해서 우선 Gaussian 형태로 불규칙한 바다 표면을 생성하였다. 풍속과 유의 파고 등에 대한 태안 앞바다에서의 실제 측정 데이터를 사용하여 이 표면을 생성하였으며, 두 변수간의 관계식을 유도함으로써 측정하기 쉬운 변수인 풍속에 의해 바다 표면 상태를 예측할 수 있는 모델을 만들었다. 평면에서의 결과를 비교함으로써 모멘트 법 모델을 검증하였고, 거친 표면의 경우에 비교적 정확한 수치 해석 방법인 Monte-Carlo/모멘트 법과 간단히 계산이 가능한 이론식인 PO 모델을 비교함으로써 거친 표면에서 PO 모델의 적용 가능한 조건을 찾아내었으며, 전파 경로 해석법을 이용하여 실제 전파의 페이딩 현상을 해석할 때에 사용되는 PO 모델의 유효성을 검증하였다.

• Journal of the Korean Data and Information Science Society
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• 제11권2호
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• pp.139-155
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• 2000

An exclusive simulation study is conducted in computing means for order statistics in standard normal variate. Monte Carlo moments are used in Shapiro-Francia W' statistic computation. Finally, quantiles for Shapiro-Francia W' are generated. The study shows that in computing means for order statistics in standard normal variate, complicated distributions and intensive numerical integrations can be avoided by using Monte Carlo simulation. Lack of accuracy is minimal and computation simplicity is noteworthy.

• 산업경영시스템학회지
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• 제32권3호
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• pp.99-109
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• 2009

Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

• 한국농공학회논문집
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• 제46권4호
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• pp.25-36
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• 2004

This study was conducted to derive the design rainfall by the consecutive duration using the at-site frequency analysis. Using the errors, K-S tests and LH-moment ratios, Log Pearson type 3 (LP3) and Generalized Extreme Value (GEV) distributions of Gamma and Non-Gamma Family, respectively were identified as the optimal probability distributions among applied distributions. Parameters of GEV and LP3 distributions were estimated by the method of L and LH-moments and the Indirect method of moments respectively. Design rainfalls following the consecutive duration were derived by at-site frequency analysis using the observed and simulated data resulted from Monte Carlo techniques. Relative root-mean-square error (RRMSE) and relative efficiency (RE) in RRMSE for the design rainfall derived by at-site analysis in the observed and simulated data were computed and compared. It has shown that at-site frequency analysis by GEV distribution using L-moments is confirmed as more reliable than that of GEV and LP3 distributions using LH-moments and Indirect method of moments in view of relative efficiency.

• 한국농공학회지
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• 제43권5호
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• pp.70-82
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• 2001

This study was conducted to derive the regional design rainfall by the regional frequency analysis based on the regionalization of the precipitation suggested by the first report of this project. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the Generalized extreme value distribution among applied distributions. Regional and at-site parameters of the generalized extreme value distribution were estimated by the linear combination of the probability weighted moments, L-moment. The regional and at-site analysis for the design rainfall were tested by Monte Carlo simulation. Relative root-mean-square error(RRMSE), relative bias(RBIAS) and relative reduction(RR) in RRMSE were computed and compared with those resulting from at-site Monte Carlo simulation. All show that the regional analysis procedure can substantially reduce the RRMSE, RBIAS and RR in RRMSE in the prediction of design rainfall. Consequently, optimal design rainfalls following the legions and consecutive durations were derived by the regional frequency analysis.

• Structural Engineering and Mechanics
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• 제11권4호
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• pp.373-392
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• 2001

The main idea behind the paper is to present two alternative methods of homogenization of the heat conduction problem in composite materials, where the heat conductivity coefficients are assumed to be random variables. These two methods are the Monte-Carlo simulation (MCS) technique and the second order perturbation second probabilistic moment method, with its computational implementation known as the Stochastic Finite Element Method (SFEM). From the mathematical point of view, the deterministic homogenization method, being extended to probabilistic spaces, is based on the effective modules approach. Numerical results obtained in the paper allow to compare MCS against the SFEM and, on the other hand, to verify the sensitivity of effective heat conductivity probabilistic moments to the reinforcement ratio. These computational studies are provided in the range of up to fourth order probabilistic moments of effective conductivity coefficient and compared with probabilistic characteristics of the Voigt-Reuss bounds.

• ETRI Journal
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• 제38권1호
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• pp.141-148
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• 2016

This paper proposes a method to estimate directly the incoherent scattered intensity and radar cross section (RCS) from the effective permittivity of a random media. The proposed method is derived from the original concept of incoherent scattering. The incoherent scattered field is expressed as a simple formula. Therefore, to reduce computation time, the proposed method can estimate the incoherent scattered intensity and RCS of a random media. To verify the potential of the proposed method for the desired applications, we conducted a Monte-Carlo analysis using the method of moments; we characterized the accuracy of the proposed method using the normalized mean square error (NMSE). In addition, several medium parameters, such as the density of scatterers and analysis volume, were studied to understand their effect on the scattering characteristics of a random media. The results of the Monte-Carlo analysis show good agreement with those of the proposed method, and the NMSE values of the proposed method and Monte-Carlo analysis are relatively small at less than 0.05.

• Nuclear Engineering and Technology
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• 제16권2호
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• pp.97-105
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• 1984

고장수목 정점사상에 대한 이용불능도의 불화실성을 분석하기 위한 방법 및 전산코드를 개발하였으며 그 유용성을 검증하였다. 이 방법은 몬테카를로 방법과 모멘트 방법을 고장수목 축소 기법과 함께 조합하여 개발하였고 WASH-1400에 있는 고장수목과 신뢰도 자료를 이용하여 본 연구에서 개발된 코드의 효율성을 검증하였다. 몬테카를로 방법과의 비교결과 이 방법을 이응하면 계산시간을 상당히 줄일 수 있으며 충분히 정확한 결과를 얻을 수 있음을 입증하였다.

• 한국산업정보학회논문지
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• 제23권3호
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• pp.49-57
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• 2018

Cho는 확률적 활동 네트워크 분석에서 활동시간이 상호 독립적이고 정규분포를 따른다는 가정 하에서 사업완성시간의 적률 (평균, 분산, 왜도, 첨도)을 추정하기 위한 방법을 제안하였다. 본 논문에서는 활동시간의 분포가 일반적인 분포일 때 사업완성시간의 적률을 추정하기 위한 방법을 제안한다. 제안된 방법은 활동시간 분포의 이산화를 위해 적률매칭 방법을 사용하며, 사업완성시간의 계산에 사용될 활동시간을 결정하는데 이산형 역변환 방법을 사용한다. 제안된 방법은 대규모 네트워크에 적용하기 쉽고, 몬테칼로 시뮬레이션 보다 계산적으로 효율적이며, 제안된 방법의 결과는 몬테칼로 시뮬레이션에 의한 결과와 잘 일치함을 보여준다.