• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2A
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• pp.383-390
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• 2006

In this paper, a stochastic field that is compatible with Monte Carlo simulation is suggested for an expansion-based stochastic analysis scheme of weighted integral method. Through investigation on the way of affection of stochastic field function on the displacement vector in the series expansion scheme, it is noticed that the stochastic field adopted in the weighted integral method is not compatible with that appears in the Monte Carlo simulation. As generally recognized in the field of stochastic mechanics, the response variability is not a linear function of the coefficient of variation of stochastic field but a nonlinear function with increasing variability as the intensity of uncertainty is increased. Employing the stochastic field suggested in this study, the response variability evaluated by means of the weighted integral scheme is reproduced with high precision even for uncertain fields with moderately large coefficient of variation. Besides, despite the fact that only the first-order expansion is employed, an outstanding agreement between the results of expansion-based weighted integral method and Monte Carlo simulation is achieved.

• Journal of Korea Port Economic Association
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• v.31 no.3
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• pp.1-14
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• 2015

This study utilizes Monte Carlo simulation to forecast the time charter rate of vessels, the three-month Libor interest rate, and the ship demolition price, to mitigate future uncertainties involving these factors. The simulation was performed 10,000 times to obtain an exact result. For the empirical analysis - based on considerations in ordering ships in 2010-a comparison between the Monte Carlo simulation-based stochastic discounted cash flow (DCF) method and traditional DCF methods was made. The analysis revealed that the net present value obtained through Monte Carlo simulation was lower than that obtained via regular DCF methods, alerting the owners to risks and preventing them from placing injudicious orders for ships. This research has implications in reducing the uncertainties that future shipping markets face, through the use of a stochastic DCF approach with relevant variables and probability methods.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.715-721
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• 2017

기술거래 시장의 활성화에 대한 연구개발서비스 분야 종사자들의 관심이 높아지고 있으며, 특히 공공 및 민간 분야의 휴면 기술(특허)에 대한 이전 거래를 통해 불필요한 특허유지 비용을 줄이고 부가적인 기술료 창출 효과를 거둘 수 있다. 본 연구에서는 현재까지 기술이전(거래), 현물출자, 기술금융(융자, 담보대출) 등 다양한 목적으로 실무에서 활용되어 온 기술가치평가 모형의 한계점을 고민해 보고, 이에 대한 개선방안으로서 몬테카를로 최소자승법 기반의 확률론적 가치평가 모형을 제시한다. 기존의 가치평가 모형은 평가산출을 위한 입력변수의 확정적 값들에 기반하여 가치액이 산출되었으나, 대표적 기법인 현금흐름 할인법이나 로열티공제법의 경우 미래의 수익예상기간, 예상매출액 등에서는 불확실성(uncertainty)가 내재되어 있다. 따라서 특정 분포(distribution)에 대한 확률론적 가능성을 가정하고 이에 대한 수학적 최적화 논리로부터 몬테카를로 최소자승 관게에 의한 변수결정 및 가치평가액 산정을 할 수 있는 평가모듈을 개발한다. 향후 연구에서는 기 평가된 사례결과를 딥러닝(deep learning) 방식으로 학습하여, 발생가능성 높은 각 변수값의 범위들을 산출하고 이로부터 기술가치 범위를 추론하는 시스템을 개발하는 것도 가능할 것으로 기대된다.

• Journal of the Korea Safety Management & Science
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• v.2 no.1
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• pp.59-75
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• 2000

최근의 추세를 볼 때 위험관리에 관한 중요성이 점점 증대하고 있다. 그럼에도 불구하고 우리나라 은행들의 위험관리 실태는 아직 미흡한 실정이다. 그리고 대부분의 은행들이 현재 위험관리에 대응하기 위하여 ALM의 갭관리, 듀레이션관리 등을 행하고 있지만 BIS에서 중요시하고 있는 VaR의 개발과 운용은 아직 초보단계에 있다. 한국 주식포트폴리오에서 몬테카를로 시뮬레이션과 Full Variance Covariance Model의 VaR값은 비슷한 수준으로 Diagonal Model 의 VaR값 보다 작음을 알 수 있다. 이는 좀 더 정교한 계산이 요구되는 Full Variance Covariance Model의 VaR값이 보다 단순한 Diagonal Model의 VaR값 보다 정확성면에서 우수하다는 것을 보여주고 있다. 한편 이자율포트폴리오 의 경우에는 델타-감마 분석법과 몬테카를로 시뮬레이션의 경우 95% 신뢰구간의 VaR는 델타-감마 분석법이 작지만 99% 신뢰구간에서의 VaR는 몬테카를로 시뮬레이션방법이 작다는 것을 알 수 있다. 그래서 어느 한 가지 방법에 의한 VaR추정치가 가장 좋은 것이라고 단정하기 어려움을 알 수 있었다.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.210-215
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• 2004

In can occur to many problems on progressing step without close scope definition, interrelation definition between activities, resource plan, and schedule plan on planning step. But it have not closely defined performance system on planning step because of many constraints of domestic construction industry. Therefore this paper intends to discuss a method of calculating optimal cost and duration using Linear Programming that solves maximing or minimizing problems among decision making methodology and Monte Carlo Simulation that decreases to probability errors. With outcoms applying Linear programming and Monte Carlo Simulation for calculating optimal cost and duration, follow as : With outcomes applying Monte Carlo Simulation, it could calculate reliable estimator about project duration through removing various constraints. With outcomes applying Linear programming, it could calculate optimal value about project cost through defining various variables and constraints on many activities.

• Journal of the Korea Concrete Institute
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• v.22 no.4
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• pp.595-603
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• 2010

Monte-Carlo simulation technique is often used in order to predict service life of concrete structure subjected to chloride penetration in marine environment based on probability theory. Monte-Carlo simulation method, however, the method gives different results every time that the simulation is run. On the other hand, moment method, which is frequently used in reliability analysis, needs negligible computational cost compared with simulation technique and gives a constant result for the same problem. Thus, in this study, moment method was applied to the calculation of corrosion-initiation probability. For this purpose, computer programs to calculate failure probabilities are developed using first-order second moment (FOSM) and second-order second moment (SOSM) methods, respectively. From the analysis examples with the developed programs, SOSM was found to give a more accurate result than FOSM does. The sensitivity analysis has shown that the factor affecting the corrosion-initiation probability the most was the cover depth, and the corrosion-initiation probability was influenced more by its coefficient of variation than its mean value.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.5
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• pp.580-586
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• 2004

The ray effects of finite volume method (FVM) or discrete ordinate method (DOM) are known to show a non-physical oscillation in solution of radiative heat transfer on a boundary. This wiggling behavior is caused by the finite discretization of the continuous control angle. This article proposes a combined procedure of the Monte-Carlo and finite-volume method (CMCFVM) for solving radiative heat transfer in absorbing, emitting, and an-isotropically scattering medium with an isolated boundary heat source. To tackle the problem, which is especially pronounced in a medium with an isolated heat source, the CMCFVM is suggested here and successfully applied to a two-dimensional circular geometry.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.406-412
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• 2010

In this paper, we formally define the problem of maximizing the coverage of sensor deployment, which is the optimization problem appeared in real-world sensor deployment, and analyze the properties of its solution space. To solve the problem, we proposed novel genetic algorithms, and we could show their superiority through experiments. When applying genetic algorithms to maximum coverage sensor deployment, the most important issue is how we evaluate the given sensor deployment efficiently. We could resolve the difficulty by using Monte Carlo method. By regulating the number of generated samples in the Monte Carlo evaluation of genetic algorithms, we could also reduce the computing time significantly without loss of solution quality.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.2
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• pp.129-140
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• 1999

추계론적 해석은 구조계 내의 해석인수에 존재하는 공간적 또는 시간적 임의성이 구조계 반응에 미치는 영향에 대한 고찰을 목적으로 한다. 확률장은 구족계 내에서 특정한 확률분포를 가지는 것으로 가정된다. 구조계 반응에 대한 이들 확률장의 영향 평가를 위하여 통계학적 추계론적 해석과 비통계학적 추계론적 해석이 사용되고 있다. 본 연구에서는 비통계학적 추계론적 해석방법 중의 하나인 가중적분법을 제안하였다. 특히 구조계의 공간적 임의성이 큰 특성을 가지고 있는 반무한영역에 대한 적용 예를 제시하고자 한다. 반무한영역의 모델링에는 무한요소를 사용하였다. 제안된 방법에 의한 해석 결과는 통계학적 방법인 몬테카를로 방법에 의한 결과와 비교되었다. 제안된 가중적분법은 자기상관함수를 사용하여 확률장을 고려하므로 무한영역의 고려에 따른 해석의 모호성을 제거할 수 있다. 제안방법과 몬테카를로 방법에 의한 결과는 상호 잘 일치하였으며 공분산 및 표준편차는 무한요소의 적용에 의하여 매우 개선된 결과를 나타내었다.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.3
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• pp.48-58
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• 1999

In this paper, a new parallel computation method, which fully utilize the parallel processors both in mesh generation and FEM calculation for 2D/3D process simulation, is presented. High performance parallel FEM and parallel linear algebra solving technique was showed that excessive computational requirement of memory size and CPU time for the three-dimensional simulation could be treated successively. Our parallelized numerical solver successfully interpreted the transient enhanced diffusion (TED) phenomena of dopant diffusion and irregular shape of R-LOCOS within 15 minutes. Monte Carlo technique requires excessive computational requirement of CPU time. Therefore high performance parallel solving technique were employed to our cascade sputter simulation. The simulation results of Our sputter simulator allowed the calculation time of 520 sec and speedup of 25 using 30 processors. We found the optimized number of ion injection of our MC sputter simulation is 30,000.