• 대한자원환경지질학회:학술대회논문집
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• 대한자원환경지질학회 2002년도 춘계 공동학술발표회
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• pp.167-169
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• 2002

The extended Born, or localized nonlinear approximation of integral equation (IE) solution has been applied to inverting single-hole electromagnetic (EM) data using a cylindrically symmetric model. The extended Born approximation is less accurate than a full solution but much superior to the simple Born approximation. When applied to the cylindrically symmetric model with a vertical magnetic dipole source, however, the accuracy of the extended Born approximation is greatly improved because the electric field is scalar and continuous everywhere. One of the most important steps in the inversion is the selection of a proper regularization parameter for stability. Occam's inversion (Constable et al., 1987) is an excellent method for obtaining a stable inverse solution. It is extremely slow when combined with a differential equation method because many forward simulations are needed but suitable for the extended Born solution because the Green's functions, the most time consuming part in IE methods, are repeatedly re-usable throughout the inversion. In addition, the If formulation also readily contains a sensitivity matrix, which can be revised at each iteration at little expense. The inversion algorithm developed in this study is quite stable and fast even if the optimum regularization parameter Is sought at each iteration step. Tn this paper we show inversion results using synthetic data obtained from a finite-element method and field data as well.

• 방송공학회논문지
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• 제2권1호
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• pp.65-73
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• 1997

본 논문에서는 대용량 지형 정보 데이터를 효과적으로 3차원 도시하기 위하여 wavelet 변환을 이용한 효과적이고 새로운 삼각형 메쉬 근사 기법과 압축 저장 기법을 제안한다. 제안된 방법은 wavelet 변환 계수의 공간-주파수 지역제한 특성을 이용하여 지형정보 데이터를 영역분할하고 각 영역에 대해 삼각형 메쉬를 생성하므로써 계산량이 적고 알고리즘이 간단하다는 장점이 있다. 또한 Embedded Zerotree Wavelet 부호화 기법을 도입하여 지형 정보데이터의 효과적인 저장, 관리는 물론 삼각형 메쉬 구성기법에 적용하였다. 제안된 지형정보 데이터의 3차원 고속도시기에는 데이터 압축, 저장 및 Level of Detail 구현에 이르는 모든 기법을 통합되었으며 모의실험을 통하여 높은 PSNR, 고속 수행, 간단한 구현 등의 장점들을 갖는 것이 확인되었다.

• 제어로봇시스템학회논문지
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• 제15권11호
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• pp.1137-1143
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• 2009

This paper presents the FPGA implementation of efficient algorithms for approximating exponential function based on floating point format data. The Taylor-Maclaurin expansion as a conventional approximation method becomes inefficient since high order expansion is required for the large number to satisfy the approximation error. A format converter is designed to convert fixed data format to floating data format, and then the real number is separated into two fields, an integer field and an exponent field to separately perform mathematic operations. A new assembly command is designed and added to previously developed command set to refer the math table. To test the proposed algorithm, assembly program has been developed. The program is downloaded into the Altera DSP KIT W/STRATIX II EP2S180N Board. Performances of the proposed method are compared with those of the Taylor-Maclaurin expansion.

• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.497-504
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• 2008

In this paper we studied the saddlepoint approximations to the distribution of quadratic forms in normal variables. We derived the approximations as a special case of Na & Kim (2005). Also applications to a statistic which concerns intraclass correlation coefficient are presented. Simulations show the accuracy and availability of the suggested approximations.

• Communications for Statistical Applications and Methods
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• 제19권4호
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• pp.597-605
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• 2012

Evidence framework enables us to determine the tuning constant in a penalized likelihood formula. We apply the framework to the estimating parameters of normal mixtures. Evidence, which is a solely data-dependent measure, can be evaluated by Laplace approximation. According to a synthetic data simulation, we found that the proper values of the tuning constant can be systematically obtained.

• Journal of the Korean Data and Information Science Society
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• 제7권2호
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• pp.189-201
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• 1996

In this paper, we study the saddlepoint approximations for the ratio of independent random variables. In Section 2, we derive the saddlepoint approximation to the density. And in Section 3, we derive two approximation formulae for the tail probability, one by following Daniels'(1987) method and the other by following Lugannani and Rice's (1980). In Section 4, we represent some numerical examples which show that the errors are small even for small sample size.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.965-971
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• 2004

In this paper we consider several nonparametric estimators for the mean residual life by using the partial moment approximation under the proportional hazard model. Also we compare the magnitude of mean square error of the proposed nonparametric estimators for mean residual life under the proportional hazard model.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1331-1336
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• 2008

This paper suggests a method using Bayesian inference to estimate the parameters of Weibull distribution and acceleration parameters under the condition that the stresses are time-dependent functions. A Bayesian model based on the discrete time approximation is formulated to infer the parameters of interest from the failure data of the virtual tests and a statistical analysis is considered to decide the most probable mean values of the parameters for reasoning of the failure data.

• Journal of the Korean Data and Information Science Society
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• 제24권1호
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• pp.179-187
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• 2013

Bates and Watts (1981) have discussed the problems of reparameterizing nonlinear models in obtaining accurate linear approximation confidence regions for the parameters. A similar problem exists with computing confidence curves for fitted values or predictions. The statistical behavior of fitted values does not depend on the parameterization. Thus, as long as the intrinsic curvature is small, standard Wald intervals for fitted values are likely to be sufficient. Accuracy of linear approximation for fitted values is investigated using confidence curves.

• 대한안전경영과학회지
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• 제8권3호
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• pp.1-9
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• 2006

Recently data mining techniques have been used for analysis and classification of data related to industrial accidents. The main objective of this study is to compare algorithms for data analysis of industrial accidents and this paper provides an optimal predicting model of 5 kinds of algorithms including CHAID, CART, C4.5, LR (Logistic Regression) and NN (Neural Network) with ROC chart, lift chart and response threshold. Also, this paper provides an approximation model for an optimal predicting model based on NN. The approximation model provided in this study can be utilized for easy interpretation of data analysis using NN. This study uses selected ten independent variables to group injured people according to a dependent variable in a way that reduces variation. In order to find an optimal predicting model among 5 algorithms, a retrospective analysis was performed in 67,278 subjects. The sample for this work chosen from data related to industrial accidents during three years ($2002\;{\sim}\;2004$) in korea. According to the result analysis, NN has excellent performance for data analysis and classification of industrial accidents.