• Journal of the Korean Data and Information Science Society
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• 제9권2호
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• pp.165-172
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• 1998

This paper considers a linear regression model with censored data where each error term follows a multivariate normal distribution. In this paper we consider the diffuse prior distribution for parameters of the linear regression model. With censored data we derive the full conditional densities for parameters of a multiple regression model in order to obtain the marginal posterior densities of the relevant parameters through the Gibbs Sampler, which was proposed by Geman and Geman(1984) and utilized by Gelfand and Smith(1990) with statistical viewpoint.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2000년도 추계학술발표회 논문집
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• pp.267-269
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• 2000

Using the fuzzified coefficients, ARMA processes can be extended to fuzzy time series model. In this paper, the estimation of parameters in the fuzzy time series model with asymmetric triangular fuzzy coefficients is studied. Nonlinear programming is applied to get solutions of parameters.

• 품질경영학회지
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• 제9권2호
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• pp.2-9
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• 1981

This paper deals with the critical role when adjustments of the regression model parameters play in forecasting. It attempts to formulate a methodology or systematic procedure for (1) detecting the points of adjustments and (2) finding the adjusted regression model parameters. The paper shows how the information of past experience in forecasting can be used future forecasting.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.1123-1134
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• 2007

This article addresses the problem of testing whether the shape parameters in k independent Weibull populations are equal. We propose a Bayesian model selection procedure for equality of the shape parameters. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the objective Bayesian model selection procedure based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Simulation study and a real example are provided.

• 산업경영시스템학회지
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• 제29권1호
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• pp.72-75
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• 2006

Event trees are widely used graphical tool to denote the accident inintiation and escalation to more severe accident. But they have some drawbacks in that they do not have efficient way of updating model parameters and also they can not contain the information about dependency or independency among model parameters. A tool that can cure such drawbacks is an influence diagram. We introduce influence diagrams and explain how to update model parameters and obtain predictive distributions. We show that an event tree can be converted to a statistically equivalent influence diagram, and bayesian prediction can be made more effectively through the use of influence diagrams.

• Journal of applied mathematics & informatics
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• 제4권1호
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• pp.135-135
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• 1997

Times series modeling plays an important role in the field of engineering, Statistics, Biomedicine etc. Model identification is one of crucial steps in the modeling of an AutoRegreesive Moving Average(ARMA(p, q)) process for real world problems. Many techniques have been developed in the literature (Salas et al., McLeod et al. etc.) for the identification of an ARMA(p, q) Model. In this paper, a new technique called The Generalised Parameters Technique is formulated for seasonal and non-seasonal ARMA model identification. This technique is very simple and can e applied to any given time series. Initial estimates of the AR parameters of the ARMA model are also obtained by this method. This model identification technique is validated through many theoretical and simulated examples.

• Elastomers and Composites
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• 제45권4호
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• pp.250-255
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• 2010

비뉴톤 점탄성 Maxwell 요소와 탄성 스프링으로 이루어진 3 요소 비뉴톤 모델로부터 응력완화 식을 유도하였다. 이 식을 응력완화 실험 결과에 적용하여 여러 가지 모델 파라메타를 계산하였다. 모델 파라메타로부터 계산한 이론 곡선은 실험적인 응력완화 곡선과 잘 일치하였다. 비선형 점탄성 모델 파라메타로부터 섬유고분자 물질의 홀부피, 미세구조, 점탄성성질, 역학적인 성질 등을 연구하였다. 응력완화 실험은 용매기를 부착한 인장 시험기를 사용하였으며, 시료는 두 종류의 polyacrylonitrile-polyvinylchloride 공중합체와 또 다른 두 종류의 PVC 모노 필라멘트 섬유를 여러 온도의 공기와 물속에서 응력완화 실험을 하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2908-2910
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• 1999

In this paper, a fuzzy model is identified and optimized using the hybrid algorithm and HCM clustering method. Here, the hybrid algorithm is carried out as the structure combined with both a genetic algorithm and the improved complex method. The one is utilized for determining the initial parameters of membership function, the other for obtaining the fine parameters of membership function. HCM clustering algorithm is used to determine the confined region of initial parameters and also to avoid overflow phenomenon during auto-tuning of hybrid algorithm. And the standard least square method is used for the identification of optimum consequence parameters of fuzzy model. Two numerical examples are shown to evaluate the performance of the proposed model.

• Journal of Welding and Joining
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• 제29권2호
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• pp.94-101
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• 2011

A lumped mass damped vibratory model was proposed for quantitative understanding of welding machine characteristics. An experimental setup was developed to determine the mechanical parameters (moving mass m, equivalent stiffness k and damping c) which govern the dynamic mechanical response of the resistance spot welding machine. During the test, acceleration of the electrodes for each level of applied load was measured by accelerometer, filtered and numerically integrated to find the corresponding velocity and displacement. The machine dynamic parameters were determined by finding the unknowns of the proposed model with experimental data. A Simulink model was proposed to investigate the influence of these mechanical parameters on the welding process. The electrode response was simulated by changing values of stiffness and damping. It was observed that both of the machine parameters(c, k) have significant effect on the response of electrode head.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2002년도 춘계 학술발표회 논문집
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• pp.20-27
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• 2002

Conventional Levenberg-Marquardt's nonlinear inversion method is simply modified by taking into account the second derivatives of the Hessian matrix so as to give robust inversion results. The weight of the second derivative terms is determined by the value of so-called λ in Levenberg-Marquardt's method. The new inversion method is applied to observed data from small-to-moderate earthquakes to simultaneously evaluate the modes parameters of the stochastic point-source model in and around the Korean Peninsula. Best estimates of the stochastic model parameters are obtained along with their statistics and compared with the previous results. Overall characteristics of the model parameters are found to be more of those of interplate than intraplate tectonic region.