• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.2
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• pp.69-79
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• 2008

Multigrid methods finite element/finite volume methods and their convergence properties are reviewed in a general setting. Some early theoretical results in simple finite element methods in variational setting method are given and extension to nonnested-noninherited forms are presented. Finally, the parallel theory for nonconforming element[13] and for cell centered finite difference methods [15, 23] are discussed.

• Journal of applied mathematics & informatics
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• v.33 no.1_2
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• pp.193-201
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• 2015

In this paper, we present preconditioned generalized accelerated overrelaxation (GAOR) methods for solving weighted linear least square problems. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the preconditioned GAOR methods converge faster than the GAOR method whenever the GAOR method is convergent. Finally, we give a numerical example to confirm our theoretical results.

• Journal of applied mathematics & informatics
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• v.6 no.1
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• pp.89-98
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• 1999

We propose some new iterative methods for solving the generalized variational inequalities where the underlying operator T is monotone. These methods may be viewed as projection-type meth-ods. Convergence of these methods requires that the operator T is only monotone. The methods and the proof of the convergence are very simple. The results proved in this paper also represent a signif-icant improvement and refinement of the known results.

• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.663-677
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• 2010

In this paper, the generalized SOR-like methods are presented for solving the saddle point problems. Based on the SOR-like methods, we introduce the uncertain parameters and the preconditioned matrixes in the splitting form of the coefficient matrix. The necessary and sufficient conditions for guaranteeing its convergence are derived by giving the restrictions imposed on the parameters. Finally, numerical experiments show that this methods are more effective by choosing the proper values of parameters.

• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.773-781
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• 2010

Recently, Yun [8] proposed a new three-step iterative method with the fourth-order convergence for solving nonlinear equations. By using his ideas, we develop a general form of multi-step iterative methods with higher order convergence for solving nonlinear equations, and then we study convergence analysis of the multi-step iterative methods. Lastly, some numerical experiments are given to illustrate the performance of the multi-step iterative methods.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.141-146
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• 2005

Ensemble method has been known as one of the most powerful classification tools that can improve prediction accuracy. Ensemble method also has been understood as ‘perturb and combine’ strategy. Many studies have tried to develop ensemble methods by improving perturbation. In this paper, we propose two new ensemble methods that improve combining, based on the idea of pattern matching. In the experiment with simulation data and with real dataset, the proposed ensemble methods peformed better than bagging. The proposed ensemble methods give the most accurate prediction when the pruned tree was used as the base learner.

• Proceedings of the KSR Conference
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• 2002.10a
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• pp.566-573
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• 2002

In this paper, is propose to the object(human) dection method using geometrical structures and projection histograms in the image. The problem of existing methods for objects tracking of background subtracted is resulted from uncertainty at background unfixed. In this paper, two methods are applied to solve problem. This problems are proved by method. This problems is demonstrated by using this methods and applied to the train railroad crossing. Therefore, this paper aims that this contributes to improve the accident of the train railroad crossing.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.7 no.2
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• pp.95-111
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• 2003

BDM mixed methods are obtained for a good approximation of velocity for flow equations. In this paper, we study an implementation issue of solving the algebraic system arising from the BDM mixed finite elements. First we discuss post-processing based on the use of Lagrange multipliers to enforce interelement continuity. Furthermore, we establish an equivalence between given mixed methods and projection finite element methods developed by Chen. Finally, we present the implementation of the first order BDM on rectangular grids and show it is as simple as solving the pressure equation.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.23 no.3
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• pp.179-202
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• 2019

This paper presents second derivative generalized extended backward differentiation formulas (SDGEBDFs) based on the second derivative linear multi-step formulas of Cash [1]. This class of second derivative linear multistep formulas is implemented as boundary value methods on stiff problems. The order, error constant and the linear stability properties of the new methods are discussed.

• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.135-150
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• 2021

We propose principal differential analysis based classification methods. Computations of squared multiple correlation function (RSQ) and principal differential analysis (PDA) scores are reviewed; in addition, we combine principal differential analysis results with the logistic regression for binary classification. In the numerical study, we compare the principal differential analysis based classification methods with functional principal component analysis based classification. Various scenarios are considered in a simulation study, and principal differential analysis based classification methods classify the functional data well. Gene expression data is considered for real data analysis. We observe that the PDA score based method also performs well.