• Communications for Statistical Applications and Methods
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• 제23권1호
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• pp.85-91
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• 2016

Aggregate claim amounts with a large claim frequency represent a major concern to automobile insurance companies. In this paper, we show that a new hybrid method to combine the analytical saddlepoint approximation and Monte Carlo simulation can be an efficient computational method. We provide numerical comparisons between the hybrid method and the usual Monte Carlo simulation.

• 대한기계학회논문집A
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• 제26권12호
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• pp.2483-2491
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• 2002

This study presents an efficient method for robust optimal design. In order to avoid the excessive evaluations of the exact performance functions, two-point diagonal quadratic approximation method is employed for approximating them during optimization process. This approximation method is one of the two point approximation methods. Therefore, the second order sensitivity information of the approximated performance functions are calculated by an analytical method. As a result, this enables one to avoid the expensive evaluations of the exact $2^{nd}$ derivatives of the performance functions unlike the conventional robust optimal design methods based on the gradient information. Finally, in order to show the numerical performance of the proposed method, one mathematical problem and two mechanical design problems are solved and their results are compared with those of the conventional methods.

• 품질경영학회지
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• 제34권3호
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• pp.19-30
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• 2006

For highly reliable products, it is difficult to assess the lifetime of the products with traditional life tests. Accordingly, a recent approach is to observe the performance degradation of product during the test rather than regular failure time. This study compares performances of three methods(i.e. the approximation, analytical and numerical methods) to estimate the parameters and quantiles of the lifetime when the time-to-failure distribution follows Weibull and lognormal distributions under a random coefficient degradation rate model. Numerical experiments are also conducted to investigate the effects of model error such as measurements in a random coefficient model.

• 터널과지하공간
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• 제22권2호
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• pp.86-92
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• 2012

점추정법은 exact probabilistic method로 간주되는 Monte Carlo simulation에 비해 계산의 정확도는 다소 떨어지지만, 성능함수의 통계 모멘트를 분석하기 위한 샘플링 수를 크게 줄일 수 있는 해석 과정에서의 간편함과 비교적 정확한 통계 모멘트의 계산으로 인해 지반 및 암반공학에서의 확률론적 신뢰성 평가에 자주 사용되고 있다. 본 연구에서는 Rosenblueth와 Zhou & Nowak의 점추정법과 Monte Carlo simulation의 계산 결과를 비교 분석하여 점추정법의 정확도와 적용성을 조사하였다. 비교 분석은 해석적 해가 주어진 탄성 지반내 원형터널의 라이닝 지보 문제를 대상으로 하였다. 분석 결과, 해석적 해가 비선형 함수임에도 불구하고, 점추정법과 Monte Carlo simulation에 의해 계산된 통계 모멘트가 평균 약 1-2%의 오차를 보여 수치해석과 연계한 지하구조물의 확률론적 신뢰성 평가를 위한 점추정법의 적용성을 확인하였다.

• Asian-Australasian Journal of Animal Sciences
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• 제11권6호
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• pp.642-647
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• 1998

A Poisson error model as a generalized linear mixed model (GLMM) has been suggested for genetic analysis of counted observations. One of the assumptions in this model is the normality for random effects. Since this assumption is not always appropriate, a more flexible model is needed. For count traits, a Poisson hierarchical generalized linear model (HGLM) that does not require the normality for random effects was proposed. In this paper, a Poisson-Gamma HGLM was examined along with corresponding analytical methods. While a difficulty arises with Poisson GLMM in making inferences to the expected values of observations, it can be avoided with the Poisson-Gamma HGLM. A numerical example with simulated embryo yield data is presented.

• Advances in aircraft and spacecraft science
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• 제9권5호
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• pp.367-375
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• 2022

Modeling the properties of complex alloys such as nickel superalloys is an extremely challenging scientific and engineering task. The model should take into account a large number of uncorrelated factors, for many of which information may be missing or vague. The individual contribution of one or another chemical element out of a dozen possible ligants cannot be determined by traditional methods. Moreover, there are no general analytical models describing the influence of elements on the characteristics of alloys. Artificial neural networks are one of the few statistical modeling tools that can account for many implicit correlations and establish correspondences that cannot be identified by other more familiar mathematical methods. However, such networks require careful tuning to achieve high performance, which is time-consuming. Data preprocessing can make model training much easier and faster. This article focuses on combining physics-based deep network configuration and input data engineering to simulate the solvus temperature of nickel superalloys. The used deep artificial neural network shows good simulation results. Thus, this method of numerical simulation can be easily applied to such problems.

• Journal of Mechanical Science and Technology
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• 제17권8호
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• pp.1148-1155
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• 2003

The finite element method is one of the methods widely applied for predicting vibration in mechanical structures. In this paper, the effect of the mesh size of the finite element model on the accuracy of the numerical solutions of the structural vibration problems is investigated with particular focus on obtaining the optimal mesh size with respect to the solution accuracy and computational cost. The vibration response parameters of the natural frequency, modal density, and driving point mobility are discussed. For accurate driving point mobility calculation, the decay method is employed to experimentally determine the internal damping. A uniform plate simply supported at four corners is examined in detail, in which the response parameters are calculated by constructing finite element models with different mesh sizes. The accuracy of the finite element solutions of these parameters is evaluated by comparing with the analytical results as well as estimations based on the statistical energy analysis, or if not available, by testing the numerical convergence. As the mesh size becomes smaller than one quarter of the wavelength of the highest frequency of interest, the solution accuracy improvement is found to be negligible, while the computational cost rapidly increases. For mechanical structures, the finite element analysis with the mesh size of the order of quarter wavelength, combined with the use of the decay method for obtaining internal damping, is found to provide satisfactory predictions for vibration responses.

• 천문학논총
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• 제30권2호
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• pp.321-325
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• 2015

Determining the absolute neutrino mass scale and the neutrino mass hierarchy are central goals in particle physics, with important implications for the Standard Model. However, the final answer may come from cosmology, as laboratory experiments provide measurements for two of the squared mass differences and a stringent lower bound on the total neutrino mass - but the upper bound is still poorly constrained, even when considering forecasted results from future probes. Cosmological tracers are very sensitive to neutrino properties and their total mass, because massive neutrinos produce a specific redshift-and scale-dependent signature in the power spectrum of the matter and galaxy distributions. Stringent upper limits on ${\sum}m_v$ will be essential for understanding the neutrino sector, and will nicely complement particle physics results. To this end, we describe here a series of cosmological hydrodynamical simulations which include massive neutrinos, specifically designed to meet the requirements of the Baryon Acoustic Spectroscopic Survey (BOSS) and focused on the Lyman-${\alpha}$ ($Ly{\alpha}$) forest - also a useful theoretical ground for upcoming surveys such as SDSS-IV/eBOSS and DESI. We then briefly highlight the remarkable constraining power of the $Ly{\alpha}$ forest in terms of the total neutrino mass, when combined with other state-of-the-art cosmological probes, leaving to a stringent upper bound on ${\sum}m_v$.