• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.467-474
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• 2006

In this paper we present a weighted support vector machine(SVM) and a weighted least squares support vector machine(LS-SVM) for the prediction in the heteroscedastic regression model. By adding weights to standard SVM and LS-SVM the better fitting ability can be achieved when errors are heteroscedastic. In the numerical studies, we illustrate the prediction performance of the proposed procedure by comparing with the procedure which combines standard SVM and LS-SVM and wild bootstrap for the prediction.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.3.2-3
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• 2003

We propose a method of surface extension method using several functions. Interpolation theory is well developed in curve and surface. But extrapolation theory is not well developed because it is not unique outside the useful domain. It requires continuous, first derivative, second derivative continuous extension for matching in NC(Numerical Control) machine. In the past, we generate data outside the useful area and refit those data using least squares method. this has some problems which have some errors within the useful area. We keep the useful area and extend the unuseful area by a function

• Bulletin of the Korean Mathematical Society
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• v.53 no.1
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• pp.247-262
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• 2016

We propose and analyze spectral and pseudo-spectral Jacobi-Galerkin approaches for weakly singular Volterra integral equations (VIEs). We provide a rigorous error analysis for spectral and pseudo-spectral Jacobi-Galerkin methods, which show that the errors of the approximate solution decay exponentially in $L^{\infty}$ norm and weighted $L^2$-norm. The numerical examples are given to illustrate the theoretical results.

• Journal of applied mathematics & informatics
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• v.2 no.2
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• pp.13-20
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• 1995

The goal of this paper is to show that the linear approxi-mation in evaluation of functions may be effectively replaced by the ex-ponential approximation formulas obtained by numerical quadratures and in the instance the relative errors can be estimated without know-ing the true values.

• Korean Journal of Mathematics
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• v.26 no.3
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• pp.467-481
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• 2018

In this paper we present a postprocessing scheme for the Raviart-Thomas mixed finite element approximation of the second order elliptic eigenvalue problem. This scheme is carried out by solving a primal source problem on a higher order space, and thereby can improve the convergence rate of the eigenfunction and eigenvalue approximations. It is also used to compute a posteriori error estimates which are asymptotically exact for the $L^2$ errors of the eigenfunctions. Some numerical results are provided to confirm the theoretical results.

• Journal of the Korean Mathematical Society
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• v.40 no.6
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• pp.1075-1083
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• 2003

The purpose of this paper is to investigate the piecewise wise polynomial approximation for the curved boundary. We analyze the error of an approximated solution due to this approximation and then compare the approximation errors for the cases of polygonal and piecewise polynomial approximations for the curved boundary. Based on the results of analysis, p-version numerical methods for solving Dirichlet's problems are applied to any smooth curved domain.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.611-620
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• 1999

We shall propose several estimators and confidence intervals for the scale parameter in a uniform distribution with the presence of a generalized uniform outlier and obtain mean squared errors(MSE) for their proposed estimators. And we shall compare numerical MSE's for the proposed several estimators of the scale parameter. Also we shall compare numerically expected lengths of confidence intervals of the scale parameter in a uniform distribution with the presence of a generalized uniform outlier.

• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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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.

• 전기의세계
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• v.28 no.3
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• pp.57-64
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• 1979

The static state estimation are divided into two groups; estimation and detection & identification. This paper centers on detection and identification algorithm. Especially, the identification of line errors is focused on and is performed by the extended W.L.S. algorithm with line swithching states. Here, line switching states mean the discrete values of line admittance which are influenced by unexpected line switching. The numerical results are obtained from the assumption that the noise vector is independent zero mean Gaussian random variables.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.147.2-147
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• 2001

In this paper we develop a new robust trajectory tracking control scheme without using joint velocity. The proposed controller doesn´t employ adaptation, Therefore, the construction of the controller becomed very simple. Moreover, by using numerical simulation, we make sure the effectiveness of the proposed controller in the presence of quantization errors.