• Tunnel and Underground Space
• /
• v.26 no.3
• /
• pp.201-211
• /
• 2016

A method for estimating rock joint size distribution using contained traces length distribution from 3D cylindrical window survey was suggested. To reduce the numerical error, an improved technique was applied. The accuracy was verified by referring to Monte-Carlo simulation and it was found that the error can be decreased with suitable gamma values.

• Journal of Korea Water Resources Association
• /
• v.44 no.5
• /
• pp.363-376
• /
• 2011

1-D hydrodynamic numerical models have been most widely used in the field of flood analysis. The model's input data are upstream/downstream boundaries, roughness coefficients, cross-sections, and so on, and computational distance step and time step are the most important factors in order to guarantee the computational accuracy, stability, and efficiency. In this study, a theoretical explanation is presented for the basis of the previous empirical selection criteria of cross-section's location; also, the estimation technique of computationally variable distance step is proposed to reflect the properties of flow at every computational time step. Combining this technique with 1-D unsteady numerical model, it was applied to two events of Teton dam failure flood and the Han River flood. The numerical experimental results demonstrate that the accuracy and stability is increased when used more interpolated cross-sections and show that the proposed technique of computationally variable distance step has the same order of accuracy with smaller numbers of cross-section than previous empirical selection criteria. The practical use of this technique will be possible to analyze the river floods with high efficiency as well as accuracy and stability.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.1
• /
• pp.32-37
• /
• 2020

This paper proposes a new l₁-norm-Recursive Least Squares (RLS) algorithm which is numerically more robust than the conventional l₁-norm-RLS. The l₁-norm-RLS was proposed by Eksioglu and Tanc in order to estimate the sparse acoustic channel. However the algorithm has numerical instability in the inverse matrix calculation. In this paper, we propose a new algorithm which is robust against the numerical instability. We show that the proposed method improves stability under several numerically erroneous situations.

• Magazine of the Korea Concrete Institute
• /
• v.11 no.2
• /
• pp.241-249
• /
• 1999

To estimate the compressive strength of concrete more realistically, relative large number of data are necessary. However, it is very common in practice that only limited data are available. The purpose of the present paper is therefore to propose a realistic method to estimate the compressive strength of concrete with limited data in actual site. The Bayesian method of statistical analysis has been applied to the problem of the estimation of compressive strength of concrete. The mean compressive strength is considered as the random parameter and a prior distribution is selected to enable updating of the Bayesian distribution of compressive strength of concrete reflecting both existing data and sampling observations. The updating of the Bayesian distribution with increasing data is illustrated in numerical application. It is shown that by combining prior estimation with information from site observation, more precise estimation is possible with relatively small sampling. It is also seen that the contribution of the prior in determining the posterior distribution depends on its sharpness or flatness in relation to the sharpness or flatness of the likelihood function. The present paper allows more realistic determination of concrete strength in site with limited data.

• Composites Research
• /
• v.28 no.5
• /
• pp.277-284
• /
• 2015

This paper presents a method to detect the fiber property variation of laminated GFRP plates from natural frequency response data. The combined finite element analysis using ABAQUS and the inverse algorithm described in this paper may allow us not only to detect the deteriorated elements from the mirco-mechanical point of view but also to find their numbers, locations, and the extent of damage. To solve the inverse problem using the combined method, this study uses several natural frequencies instead of mode shapes in a structure as the measured data. Several numerical results show that the proposed system is computationally efficient in identifying fiber stiffness degradation for complex structures such as composites with various layup sequences.

• The Korean Journal of Applied Statistics
• /
• v.28 no.5
• /
• pp.895-906
• /
• 2015

Diffusion is a mathematical tool to explain the fluctuation of financial assets and the movement of particles in a micro time scale. There are ongoing statistical trials to develop an estimation method for diffusion models based on likelihood. When we estimate diffusion models by applying the maximum likelihood estimation method on data observed at discrete time points, we need to know the transition density of the diffusion. In order to approximate the transition densities of diffusion models, we suggests the method to approximate the path integral of the random process with normal random variables, and compare the numerical properties of the method with other approximation methods.

• The Korean Journal of Applied Statistics
• /
• v.30 no.1
• /
• pp.95-102
• /
• 2017

Gamma generalized linear models have received less attention than Poisson and binomial generalized linear models. Therefore, many old-established statistical techniques are still used in gamma generalized linear models. In particular, existing literature and textbooks still use approximate estimates for the dispersion parameter. In this paper we study the efficiency of various dispersion parameter estimators in gamma generalized linear models and perform numerical simulations. Numerical studies show that the maximum likelihood estimator and Cox-Reid adjusted maximum likelihood estimator are recommended and that approximate estimates should be avoided in practice.

• Proceedings of the Korean Reliability Society Conference
• /
• 2000.11a
• /
• pp.315-320
• /
• 2000

본 연구에서는 수리 가능한 시스템에서 고장 강도와 수리 효과에 대한 모수 추정 문제를 다룬다. 시스템이 노후화로 인한 고장이 발생할 경우 최소수리가 행해지고 계획된 예방정비에서는 비례적 수명 감소가 이루어지는 수명 데이터에 대해서 고장 강도 함수의 모수와 정비의 수리효과를 추정하기 위해서 최대 우도 함수 방법을 이용한다. 또한 유전자 알고리즘을 이용해서 우도 함수를 최대화시키는 절차를 개발하고 수치 예제를 나타낸다.

• The KIPS Transactions:PartD
• /
• v.10D no.5
• /
• pp.805-812
• /
• 2003

This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP; expressions are given for several performance measure. The parametric inferences of the model using Logarithmic Poisson model, Crow model and Rayleigh model is discussed. Bayesian computation and model selection using the sum of squared errors. The numerical results of this models are applied to real software failure data. Tools of parameter inference was used method of Gibbs sampling and Metropolis algorithm. The numerical example by T1 data (Musa) was illustrated.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.22 no.52
• /
• pp.181-189
• /
• 1999

사건 가지 상의 파라메터 추정을 위한 베이지안 접근방식이 제시된다. 먼저 일반적인 사건 가지를 따라 발생하는 사고를 예측하기 위한 모형에 대해 설명한다. 이 경우 이론적으로 베이지안 기법을 적용하는 방법에 대해 논하고 실제로 문제를 풀 경우에 발생하는 다차원 수치적분 문제를 다룬다. 감마 분포와 베타분포가 이용될 경우 위 문제를 쉽게 해결할 수 있는 근사적 방법에 대해 연구한다. 또한 사건가지상의 여러 경로가 같은 수준의 사고로 분류 될 수 있는 경우에 대해서도 위와 같은 방법에 관한 연구를 한다. 결과적으로 한 사고율이 여러 개의 파라메터의 함수로 표현되어 다차원의 수치적분이 요구되는 경우 이를 쉽게 해결 할 수 있는 근사적인 방법이 제시되어 베이지안 기법의 적용이 용이해 질 수 있다.