• 한국생산제조학회지
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• 제4권3호
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• pp.39-47
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• 1995

This paper suggests generalize mathematica mode for the benefit of volumetric error analysis of a multi-axis machine tool machining a sculptured surfaces. The volumetric error, in this paper, is defined as a three dimensional error at the cutting point, which is caused by the geometric errors and the kinematic errors of each axis and alignment errors of the cutting tool. The actual cutting position is analyzed based on the form shaping model including a geometric error of the moving carriage, where a form shaping model is derived from the homogeneous transformation matrix. Then the volumetric error is obtained by calculating the position difference between the actual cutting position and the ideal one calculated from a Nonuniform Rational B-Spline named as NURES. The simulation study shows the effectiveness for predicting the behavior of machining error and for the method of error compensation.

• Journal of the Korean Statistical Society
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• 제34권2호
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• pp.161-172
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• 2005

In this paper a nonparametric method is proposed for detecting conditionally heteroscedastic errors in a nonparametric time series regression model where the observation points are equally spaced on [0,1]. It turns out that the first-order sample autocorrelation of the squared residuals from the kernel regression estimates provides essential information. Illustrative simulation study is presented for diverse errors such as ARCH(1), GARCH(1,1) and threshold-ARCH(1) models.

• Journal of the Korean Statistical Society
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• 제33권2호
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• pp.169-189
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• 2004

Under the assumption of default priors, such as noninformative priors, Bayesian model determination and parameter estimation of regression models with stationary and invertible ARMA errors are developed under exact full likelihoods. The default Bayes factors, the fractional Bayes factor (FBF) of O'Hagan (1995) and the arithmetic intrinsic Bayes factors (AIBF) of Berger and Pericchi (1996a), are used as tools for the selection of the Bayesian model. Bayesian estimates are obtained by running the Metropolis-Hastings subchain in the Gibbs sampler. Finally, the results of numerical studies, designed to check the performance of the theoretical results discussed here, are presented.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 정기총회 및 추계학술대회 논문집 학회본부
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• pp.296-298
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• 1993

The performance of MODEL-BASED controller is influenced by model parameter errors and velocity measurement errors. To reduce this errors, Control methods by parameter adaptation and velocity estimation are studied. But because these controller has complex construction and need much computation time, the implementation of single processor system is difficult. This paper proposes a control scheme which combines an adaptive control law with a sliding observer using transputer network.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.1028-1034
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• 2003

We consider the sensitivity of average inventory cost rate when true values of the parameters In the EOQ model are unknown over known ranges. In particular, In the case that the valid range on the true economic lot size are known. we provide a formula for estimating the lot size under minimax criterion. Moreover, to estimate the valid range, we apply the propagation of errors technique. Then, we present a scheme to find a (valid) lot size. based on the estimated range of the true lot size from the propagation or errors technique.

• 한국정밀공학회지
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• 제6권2호
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• pp.88-97
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• 1989

In general turret servo system is subject to influnces by disturbances and uncertain modeling errors, which result from large dynamic characteristics and high-spedd operation. In this paper the influences of such disturbances and modeling errors are analyzed quali- tatively for the linerar approximation model of turret servo system, and then LQG/LTR control theory is applied to linear approximation model in order to design a controller which satisfies robustness/stability for the modeling errors. Finally the performance and robustness of designed controller for the given plant are verified through the simulation.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.826-829
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• 2008

In a field measurement, measurement errors are produced by measuring environments and systematic errors in the measurement procedure. Measurement errors can be expressed as a measurement uncertainty. In this study, the measurement uncertainty and various measuring factors are investigated in heavy-weight impact sounds. According to KS 2810-2, the model functions, which is the estimation of the maximum SPL measurement in each octave band frequency, are determined. From this estimation model, 3.53dB is shown in 63Hz. This level is caused by the sound field of the receiving room, which does not meet the diffusing field.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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• pp.382-387
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• 2003

In this paper, a neural networks-based damage detection method using the modal properties is presented, which can effectively reduce the effect of the modeling errors in the baseline finite element model from which the training patterns for the networks are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Results of laboratory test on a simply supported bridge model and field test on a bridge with multiple girders confirm the applicability of the present method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.54-57
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• 2002

In this paper model reference adaptive control (MRAC) of linear time-varying(LTV) systems is considered. MRAC for a linear time invariant(LTI) system does not assure the boundedness of the output and parameter estimation errors in the presence of time variations of the parameters. However, changing the adaptive laws such as use of $\sigma$-modification can result in the boundedness of the output and parameter estimation errors[5]. Together with the $\sigma$-modification in the adaptive law, we also modify the control law by adding an additional term to the standard control law. The additional term leads to smaller bounds of the output and parameter estimation errors when compared to the case where only the standard control law is applied.

• Communications for Statistical Applications and Methods
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• 제27권5호
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• pp.511-521
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• 2020

In this paper, a partially linear multivariate model with error in the explanatory variable of the nonparametric part, and an m dimensional response variable is considered. Using the uniform consistency results found for the estimator of the nonparametric part, we derive an estimator of the parametric part. The dependence of the convergence rates on the errors distributions is examined and demonstrated that proposed estimator is asymptotically normal. In main results, both ordinary and super smooth error distributions are considered. Moreover, the derived estimators are applied to the economic behaviors of consumers. Our method handles contaminated data is founded more effectively than the semiparametric method ignores measurement errors.