• Title/Summary/Keyword: Monte Carlo simulation

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The Comparison Analysis of an Estimators of Nonlinear Regression Model using Monte Carlo Simulation (몬테칼로 시뮬레이션을 이용한 비선형회귀추정량들의 비교 분석)

  • 김태수;이영해
    • Journal of the Korea Society for Simulation
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    • v.9 no.3
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    • pp.43-51
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    • 2000
  • In regression model, we estimate the unknown parameters by using various methods. There are the least squares method which is the most general, the least absolute deviation method, the regression quantile method and the asymmetric least squares method. In this paper, we will compare each others with two cases: firstly the theoretical comparison in the asymptotic sense and then the practical comparison using Monte Carlo simulation for a small sample size.

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Monte Carlo simulation of the estimators for nonlinear regression model (비선형 회귀모형 추정량들의 몬데칼로 시뮬레이션에 의한 비교)

  • 김태수;이영해
    • Proceedings of the Korea Society for Simulation Conference
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    • 2000.11a
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    • pp.6-10
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    • 2000
  • In regression model we estimate the unknown parameters using various methods. There are the least squares method which is the most general, the least absolute deviation, the regression quantile and the asymmetric least squares method. In this paper, we will compare each others with two case: to begin with the theoretical comparison in the asymptotic sense, and then the practical comparison using Monte Carlo simulation for a small sample size.

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Reliability Evaluation of Transmission System using Monte Carlo Simulation Method (Monte Carlo Simulation기법을 이용한 송전계통의 신뢰도 평가)

  • Moon, Seung-Pil;Kim, Hong-Sik;Choi, Jae-Seok;Cha, Jun-Min
    • Proceedings of the KIEE Conference
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    • 2001.05a
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    • pp.169-171
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    • 2001
  • This paper presents a method fer evaluation nodal probabilistic congestion and reliability indices of transmission systems using Monte Carlo simulation methods. Quantitative evaluation of transmission system reliability is very important because successful operation of an electric power system. In the deregulated electricity market depends on transmission system reliability management Monte Carlo methods are often preferable, when complex operating conditions are involved and/or the number of sever events is relatively large. To evaluate the reliability of a real power system, Monte Carlo Methods will be more useful. The characteristics and effectiveness of this methodology are illustrated by the case study using a small test system.

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Optimal Gamma Irradiation Using Monte Carlo Simulations on Wooden Cultural Properties, Gimjeotgae (목재 유물 김젖개의 몬테카를로 방법을 이용한 감마선 조사)

  • Yoon, Minchul;Choi, Jong-il;Lee, Yun Jong;Lim, Kil-Sung;Lee, Ju-Woon
    • Journal of Radiation Industry
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    • v.6 no.1
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    • pp.95-100
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    • 2012
  • In this study, there has been investigated the simulation of irradiation dose using Monte Carlo methodology for the biological control of wooden cultural property. In the evaluation of fungal contamination on wooden cultural properties, Cladosporium tenuissimum, Aspergillus versicolor, Penicillium sp. were mainly identified from the Gimjeotgae. But these microorganisms were completely inactivated by 20 kGy gamma-rays. For dosimetry simulation of wooden cultural properties, Monte Carlo methodology with MCNP was used. The radiation absorbed dose distribution was predicted at 8.2~18.9 kGy. These results show that irradiation is effective for biologic control of wooden cultural properties and Monte Carlo methodology is useful for non-destructive conservation and preservation of wooden cultural properties.

Experimental Measurement and Monte Carlo Simulation the Correction Factor for the Medium-Energy X-ray Free-air Ionization Chamber

  • Yu, Jili;Wu, Jinjie;Liao, Zhenyu;Zhou, Zhenjie
    • Journal of the Korean Physical Society
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    • v.73 no.10
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    • pp.1466-1472
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    • 2018
  • A key comparison has been made between the air-kerma standards of the National Institute of Metrology (NIM), China, and other Asia Pacific Metrology Programme (APMP) members in the medium-energy X-ray. This paper reviews the primary standard Free-air ionization chamber correction factor experimental method and Monte Carlo simulation method in the NIM. The experimental method and the Monte Carlo simulation method are adopted to obtain the correction factor for the medium-energy X-ray primary standard free-air ionization chamber at 100 kV, 135 kV, 180 kV, 250 kV four CCRI reference qualities. The correction factor has already been submitted to the APMP as key comparison data and the results are in good agreement with those obtained in previous studies. This study shows that the experimental method and the EGSnrc simulation method are usually used in the measurement of the correction factor. In particular, the application of the simulation methods is more common.

A Study on Monte Carlo Simulation in Resin of New Austria Tunnel Method by admixture for Shrinkage Compensating Concrete (무수축 콘크리트 혼화제를 활용한 New Austria Tunnel Method 수지에서 Monte Carlo 시뮬레이션에 관한 연구)

  • Kim, Ki-Jun;Sung, Wan-Mo;Kim, Joo-Han;Jung, Hyung-Hak
    • Journal of the Korean Applied Science and Technology
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    • v.34 no.1
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    • pp.125-131
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    • 2017
  • The influences of scatterer and absorber in turbid material by light scattering in concrete admixture were interpreted for the scattered intensity and wavelength. The molecular properties have been studied by Monte Carlo simulation in resin of New Austria Tunnel Method. It has been found that the effects of optical properties in scattering media could be investigated by the optical parameters(${\mu}_s$, ${\mu}_a$,${\mu}_t$). Monte Carlo Simulation method for modelling of light transport in the civil engineering and construction field was applied. The results using a phantom were discussed that the admixture for shrinkage compensating concrete in NATM-rasin from source to detector is measured, and scattering intensity is stronger with those obtained through Monte Carlo Simulation. It may also aid in designing the best model for coatings and corrosion for the durability of metal constructions.

A Study on Monte Carlo Simulation by Beam Scattering in Resin of New Austria Tunnel Method for Safety of Industrial Disaster (산업재해 안전을 위한 New Austria Tunnel Method 수지에서 빔산란에 관한 Monte Carlo 시뮬레이션에 관한 연구)

  • Kim, Ki-Jun;Lee, Joo-Youb
    • Journal of the Korean Applied Science and Technology
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    • v.29 no.3
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    • pp.473-479
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    • 2012
  • The influences of scatterer and absorber in turbid material by light scattering were interpreted for the scattered intensity and wavelength. The molecular properties have been studied by Monte Carlo simulation in resin of New Austria Tunnel Method. It has been found that the effects of optical properties in scattering media could be investigated by the optical parameters(${\mu}_s$, ${\mu}_a$, ${\mu}_t$). Monte Carlo Simulation method for modelling of light transport in the civil engineering and construction field was applied. The results using a phantom were discussed that the distance from source to detector is closer, and scattering intensity is stronger with those obtained through Monte Carlo Simulation. It may also aid in designing the best model for coatings and corrosion for the durability of metal constructions.

Interference Analysis based on the Monte-Carlo Method (Monte-Carlo 기반의 간섭분석에 관한 연구)

  • Kim, Seong-Kweon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.3 no.2
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    • pp.58-64
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    • 2008
  • In this paper, we proposed the methodology of interference analysis based on monte-carlo method for effective use of Industrial, Scientific, Medical (ISM) band. The interference scenario is divided according to the distance and density. The simulation of interference analysis evaluates the interference probability according to distribution density of Interfering Transmitters (It) in the Secure Interference Area (SIA). The SIA is gained from the Interference Efficiency Range that satisfied to Interference Permissible Range of Victim Receiver (Vr). Simulation result that apply the proposed interference scenario to the WLAN and bluetooth, Interference Permissible Range was 60~400m. And the WLAN was acceptable within interference permissible range to six bluetooth that exist in the SIA. In the same condition, when applied Listen Before Talk (LBT) based on Cognitive Radio (CR) to the bluetooth using Frequency Hopping (FH), interference probability was decreased sharply. The Spectrum Engineering Advanced Monte Carlo Analysis Tool (SEAMCAT) that has been developed based on the monte-carlo method by European Radio-communications Office (ERO) were used to the interference simulation.

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Bayesian Estimation of State-Space Model Using the Hybrid Monte Carlo within Gibbs Sampler

  • Park, Ilsu
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.203-210
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    • 2003
  • In a standard Metropolis-type Monte Carlo simulation, the proposal distribution cannot be easily adapted to "local dynamics" of the target distribution. To overcome some of these difficulties, Duane et al. (1987) introduced the method of hybrid Monte Carlo(HMC) which combines the basic idea of molecular dynamics and the Metropolis acceptance-rejection rule to produce Monte Carlo samples from a given target distribution. In this paper, using the HMC within Gibbs sampler, an asymptotical estimate of the smoothing mean and a general solution to state space modeling in Bayesian framework is obtaineds obtained.

MONTE CARLO DEPLETION UNDER LEAKAGE-CORRECTED CRITICAL SPECTRUM VIA ALBEDO SEARCH

  • Yun, Sung-Hwan;Cho, Nam-Zin
    • Nuclear Engineering and Technology
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    • v.42 no.3
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    • pp.271-278
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    • 2010
  • While the deterministic lattice physics/depletion codes use leakage-corrected critical spectrum (although approximate due to the B1 buckling search employed), Monte Carlo depletion codes currently in use do not have such a feature in spite of their heterogeneity and continuous-energy modeling capability. This paper describes an approach to Monte Carlo depletion with leakage-corrected critical spectrum derived from first principles. This is based on the concept of albedo eigenvalue treated as weight of the reflected neutron in Monte Carlo simulation.