• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.1006-1008
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• 2005

최근에 계산금융 분야에서 복잡한 수식을 이용한 연산이 증가하고 있다. 그리고 계산금융 분야에서 몬테카를로 시뮬레이션은 대표적인 계산방법 중에 하나이다. 그러나 몬테카를로 시뮬레이션은 많은 반복연산을 수행하므로 연산시간이 오래 걸리는 문제점이 있다. 이러한 문제점을 해결하기 위하여 본 논문에서는 몬테카를로 시뮬레이션과 스프레드시트를 병렬로 처리하였다. 또한 실험을 통하여 병렬 스프레드시트의 계산 노드가 증가함에 따라 파생상품의 계산 시간이 단축되는 것을 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.751-754
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• 2020

본 논문은 지수를 추종하기 위해 유전 알고리즘에 몬테카를로 샘플링을 추가한 방법을 제안한다. 몬테카를로 샘플링을 통해 효율적으로 축소된 탐색공간을 탐험하는 유전 알고리즘은 최적의 종목들을 선택한다. 제안된 방법을 KOSPI200 지수 추종에 대하여 실험하였다. 제안된 방법이 몬테카를로 샘플링을 사용하지 않는 유전 알고리즘에 비해 지수 추종 오차가 더 낮고 더 빠르게 수렴하는 것을 보여주었다.

• Journal of Korea Game Society
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• v.14 no.3
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• pp.47-54
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• 2014

The game of Go is one of the oldest games and originated at least more than 2,500 years ago. In game programming the most successful approach is to use game tree searches using evaluation functions. However it is really difficult to construct feasible evaluation function in computer Go. Monte-Carlo Tree Search(MCTS) has created strong computer Go programs such as MoGo and CrazyStone which defeated human Go professionals played on the $9{\times}9$ board. MCTS is based on the winning rate estimated by Monte-Carlo simulation. Prior to implementing MCTS into computer Go, we tried to measure each winning rate of three positions, center, corner and side, in Tic-Tac-Toe playing as the best first move. The experimental result revealed that the center is the best, a corner the next and a side the last as the best first move.

• 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.

• 전자공학회논문지 IE
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• v.43 no.1
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• pp.59-66
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• 2006

In this study, we have proposed a motion equation to control synchro drive mobile robot, a path plan to compute and track the best path to given destination and a technique utilizing uniform distribution and cluster management based Monte Carlo localization to have track current position of moving robot. In the localization test which was repeated 73 times resulted as following. The average process time of original Monte Carlo localization was 12.8ms. The proposed cluster management Monte Carlo localization resulted 9.3ms. Also the proposed method resulted correctly in the cases where original method failed.

• 대한방사선방어학회:학술대회논문집
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• 2010.04a
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• pp.174-175
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• 2010

• 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.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.346-352
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• 2012

Radiation dose estimation on the newborn and infants during radiation examinations, unlike for the adults, is not actively being progressed. Therefore, as an index to present exposure dose during radiation examinations on newborn and infants, entrance skin dose was measured, and the result was compared with results of monte carlo simulation to raise reproducibility of entrance skin dose measurement, and it was proved that various geometry implementation was possible. The resulting values through monte carlo simulation was estimated using normalization factors for entrance skin dose to calibrate radiation dose and then normalized to a unit X ray radiation field size. Average entrance skin dose per one time exposure was $78.41{\mu}Gy$ and the percentage error between measurement by dosimeter and by monte carlo simulation was found to be -4.77%. Entrance skin dose assessment by monte carlo simulation provides possible alternative method in difficult entrance skin dose estimation for the newborn and infants who visit hospital for actual diagnosis.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.144.1-144.1
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• 2005

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.4
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• pp.341-348
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• 2015

This paper addresses Monte-Carlo simulation analyses for the stage separation of the general launch vehicle. The stage separation event of the launch vehicle occurs during a very short time and is related with many dynamic parameters. The stage separation is a critical event in that the launch fails if there is a collision during the stage separation. The stage separation analyses was conducted for the general launch vehicle to confirm the separation without collision within the designed clearance in case of the random input parameters. This paper presents the stochastic results of the stage separation of the launch vehicle using the Monte-Carlo simulation.