• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제24권1호
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• pp.79-84
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• 2020

In this article, we implement a recently developed fast Monte Carlo simulation (MCS) for pricing equity-linked securities (ELS), which is most commonly issued autocallable structured financial derivative in South Korea, on the mobile platform. The fast MCS is based on Brownian bridge technique. Although mobile platform devices are easy to carry around, mobile platform devices are slow in computation compared to desktop computers. Therefore, it is essential to use a fast algorithm for pricing ELS on the mobile platform. The computational results demonstrate the practicability of Android application implementation for pricing ELS.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2005년도 하계학술대회 논문집 Vol.6
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• pp.578-580
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• 2005

Energy distribution function for electrons in SF6-Ar mixtures gas used by MCS-BEq algorithm has been analysed over the E/N range 30~300[Td] by a two term Boltzmann equation and by a Monte Carlo Simulation using a set of electron cross sections determined by other authors, experimentally the electron swarm parameters for 0.2[%] and 0.5[%] $SF_6$-Ar mixtures were measured by TOF method, The results show that the deduced electron drift velocities, the electron ionization or attachment coefficients, longitudinal and transverse diffusion coefficients and mean energy agree reasonably well with theoretical for a rang of E/N values. The results obtained from Boltzmann equation method and Monte Carlo simulation have been compared with present and previously obtained data and respective set of electron collision cross sections of the molecules.

• Structural Engineering and Mechanics
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• 제3권3호
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• pp.201-213
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• 1995

At present Level 2 and importance sampling methods are the main tools used to estimate reliability of structural systems. But sometimes application of these techniques to realistic problems involves certain difficulties. In order to overcome the difficulties it is suggested to use Monte Carlo simulation in combination with two other techniques-extreme value and tail entropy approximations; an appropriate Pearson's curve is fit to represent simulation results. On the basis of this approach an algorithm and computer program for structural reliability estimation are developed. A number of specially chosen numerical examples are considered with the aim of checking the accuracy of the approach and comparing it with the Level 2 and importance sampling methods. The field of application of the approach is revealed.

• 제어로봇시스템학회논문지
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• 제8권10호
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• pp.847-850
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• 2002

Stochastic process analysis is often based on Monte Carlo simulations. As a more rigorous alternative, a deterministic algorithm based on numerical integration is proposed in this paper. which calculates the probability distributions of dependent random variables using the results of simulation with grid points of independent random variables. For performance evaluation, the proposed algorithm is applied to an example problem which can be analytically solved. and the result is compared with that of Monte Carlo simulation. The proposed algorithm is suitable for general process simulation problems with a few independent random variables, and expected to be applicable to areas such as safety analysis and quality control.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.704-710
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• 2018

For the optimal design of electromagnetic device involving uncertainties in design variables, this paper proposes a new reliability-based optimal design algorithm for multiple constraints problems. Through optimizing the nominal objective function and maximizing the minimum reliability, a set of global optimal reliable solutions representing different reliability levels are obtained by the multi-objective particle swarm optimization algorithm. Applying the sensitivity-assisted Monte Carlo simulation method, the numerical efficiency of optimization procedure is guaranteed. The proposed reliability-based algorithm supplying multi-reliable solutions is investigated through applications to analytic examples and the optimal design of two electromagnetic problems.

• 감성과학
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• 제7권3호
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• pp.1-6
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• 2004

제한된 방적사의 두께신호로부터 유사구조를 갖는 다량의 데이터를 합성하는 방법이 개발되었다. 모사된 방적사의 두께신호는 넵 등의 발생횟수는 물론 발생위치에 관한 정보를 원래의 데이터와 유사하게 포함하고 있으므로, 이를 통해 모사한 직물이미지의 외관도 원래의 것과 크게 다르지 않은 특징을 가지고 있다. 몬테 카를로 모사법과 웨이블릿 변환을 결합한 알고리듬을 결합하여 개발된 방법은 넵, 두꺼운 부분, 가는 부분 등 방적사 외관상의 특징을 나타내는 요소들을 그대로 유지함으로써, 가상의 직물이미지를 모사하는 데 매우 효과적인 방법을 제공한다.

• Nuclear Engineering and Technology
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• 제35권1호
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• pp.55-63
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• 2003

Threshold porosity above which fission gas release channels would be formed in the rim egion of high burnup UO$_2$ fuel was estimated by the Monte Carlo method and Hoshen-Kopelman algorithm. With the assumption that both rim pore and rim grain can be represented by cube, pore distribution in the rim was simulated 3-dimensionally by the Monte Carlo method according to porosity and pore size distribution. Then, using the Hoshen-Kopelman algorithm, the fraction of open rim pores interlinked to the outer surface of a fuel pellet was derived as a function of rim porosity. The simulation showed that porosity of 24-25% is the threshold above which the number of rim pores forming release channels increases very rapidly. On the other hand, channels would not be formed if the porosity is less than about 23.5%. This is consistent with the observation that, for porosity less than 23.5%, almost no fission gas is released in the rim. However, once the rim porosity reaches beyond 25%, extensive open paths would be developed and considerable fission gas release would start in the rim.

• 한국위성정보통신학회논문지
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• 제9권4호
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• pp.104-110
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• 2014

본 논문에서는 무인항공기인 방송용 멀티콥터를 이용한 Full-HD급 이상 화질의 이미지를 효율적으로 전송하기 위해 이미지 압축 센싱 기법을 적용하고, Sparse 신호의 효율적 복원을 위해 Turbo 알고리즘과 Markov chain Monte Carlo (MCMC) 알고리즘의 복원 성능을 모의실험을 통해 비교 분석하였다. 제안된 복원 기법은 압축 센싱에 기반하여 데이터 용량을 줄이고 빠르고 오류 없는 원신호 복원에 중점을 두었다. 다수의 이미지 파일로 모의실험을 진행한 결과 Loopy belief propagation(BP) 기반의 Turbo 복원 알고리즘이 Gibbs sampling기반 알고리즘을 수행하는 MCMC 알고리즘 보다 평균 복원 연산 시간, NMSE 값에서 우수하여 보다 효율적인 복원 방법으로 생각된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3355-3372
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• 2022

Composing music is an inspired yet challenging task, in that the process involves many considerations such as assigning pitches, determining rhythm, and arranging accompaniment. Algorithmic composition aims to develop algorithms for music composition. Recently, algorithmic composition using artificial intelligence technologies received considerable attention. In particular, computational intelligence is widely used and achieves promising results in the creation of music. This paper attempts to provide a survey on the music generation based on the Monte Carlo (MC) algorithm. First, transform the MIDI music format files to digital data. Among these data, use the logistic fitting method to fit the time series, obtain the time distribution regular pattern. Except for time series, the converted data also includes duration, pitch, and velocity. Second, using MC simulation to deal with them summed up their distribution law respectively. The two main control parameters are the value of discrete sampling and standard deviation. Processing the above parameters and converting the data to MIDI file, then compared with the output generated by LSTM neural network, evaluate the music comprehensively.

• 한국컴퓨터그래픽스학회논문지
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• 제30권2호
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• pp.1-9
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• 2024

본 논문에서는 밀도 데이터로부터 다양한 벡터장 패턴을 시각화하는 새로운 방법을 제안한다. 이를 위해 물리 기반 시뮬레이션과 기하학적 처리에서 사용되는 이동최소제곱(Moving least squares, MLS)을 이용한다. 하지만 일반적인 MLS는 벡터기반의 제약조건을 통해 고차 보간되기 때문에 밀도의 특성을 고려하지 못한다. 본 논문에서는 입력 데이터에 내포되어 있는 밀도의 특성을 효율적으로 고려하기 위해 몬테카를로 기반의 가중치를 MLS에 통합하여 다양한 형태의 백터장을 표현할 수 있도록 알고리즘을 설계한다. 결과적으로 일반적인 MLS와 발산제약 기반의 MLS 같은 기존 기법으로는 표현하기 힘든 디테일한 벡터장을 실험을 통해 보여준다.