• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제9권2호
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• pp.55-64
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• 2005

In this paper, generalized difference methods(GDM) for one-dimensional viscoelastic problems are proposed and analyzed. The new initial values are given in the generalized difference scheme, so we obtain optimal error estimates in $L^p$ and $W^{1,p}(2\;{\leq}\;p\;{\leq}\;{\infty})$ as well as some superconvergence estimates in $W^{1,p}(2\;{\leq}\;p\;{\leq}\;{\infty})$ between the GDM solution and the generalized Ritz-Volterra projection of the exact solution.

• Journal of applied mathematics & informatics
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• 제6권1호
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• pp.15-30
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• 1999

In this paper the second order semi-discrete and full dis-crete generalized difference schemes for one dimensional parabolic equa-tions are constructed and the optimal order $H^1$ , $L^2$ error estimates and superconvergence results in TEX>$H^1$ are obtained. The results in this paper perfect the theory of generalized difference methods.

• 대한수학회지
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• 제34권3호
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• pp.515-531
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• 1997

In this paper, finite difference method is applied to approximate the generalized solutions of Sobolev equations. Using the Steklov mollifier and Bramble-Hilbert Lemma, a priori error estimates in discrete $L^2$ as well as in discrete $H^1$ norms are derived frist for the semidiscrete methods. For the fully discrete schemes, both backward Euler and Crank-Nicolson methods are discussed and related error analyses are also presented.

• Journal of applied mathematics & informatics
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• 제6권1호
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• pp.143-162
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• 1999

In this paper we consider the second order generalized difference scheme for the two-point boundary value problem and ob-tain optimal order error estimates in $L^\infty$ and $W^{1,\infty}$ The results in this paper perfect the theory of the second order generalized difference method.

• Communications for Statistical Applications and Methods
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• 제1권1호
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• pp.112-118
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• 1994

The generalized least squares estimator in the linear regression model is equivalent to difference estimator irrespective of the particular form of the regressor matrix when the disturbances are generated by a seasonally autoregressive provess and autocorrelation is closed to unity.

• Structural Engineering and Mechanics
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• 제49권1호
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• pp.41-64
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• 2014

The main objective of this article is the exploitation of a stochastic hybrid mesh-free method based on stochastic generalized finite difference (SGFD), Newmark finite difference (NFD) methods and Monte Carlo simulation for thermoelastic wave propagation and coupled thermoelasticity analysis based on GN theory (without energy dissipation). A thick hollow cylinder with Gaussian uncertainty in mechanical properties is considered as an analyzed domain for the problem. The effects of uncertainty in mechanical properties with various coefficients of variations on thermo-elastic wave propagation are studied in details. Also, the time histories and distribution on thickness of cylinder of maximum, mean and variance values of temperature and radial displacement are studied for various coefficients of variations (COVs).

• 대한토목학회논문집
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• 제14권1호
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• pp.131-141
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• 1994

특성곡선을 고려한 세가지 연산자 분리방법을 오염원의 종확산 문제에 적용하여, 그 결과를 Eulerian 기법들의 계산결과와 비교하였다. 연산자 분리방법의 이송방정식에 대한 수치 기법들로는 generalized upwind, two-point fourth-order 및 sixth-order Holly-Preissmann 기법들을 각각 적용하였으며, 확산 방정식에 대한 수치기법으로는 Crank-Nicholson 기법을 적용하였다. Holly-Preissmann 기법을 사용하는 연산자 분리방법들이 Eulerian 기법들에 비하여 매우 정확한 계산결과를 나타내었다. Eulerian 기법들의 경우에는 이송항의 근사방법으로서 중앙차분을 취하는 기법들은 수치진동을, 후방차분을 취하는 기법들은 수치분산을 각각 보였으며, 이러한 현상들은 종확산계수의 값이 작을수록 더욱 뚜렷하게 나타났다.

• Communications for Statistical Applications and Methods
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• 제17권2호
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• pp.275-292
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• 2010

동일 환자에게 적용된 2가지 진단검사의 정확성을 비교하기 위한 방법들 중에서 두개의 ROC곡선 아래 면적(AUC; Area Under Curve)의 차이는 주요한 잣대 중 하나이다. 본 연구에서는 AUC의 차이를 추정하는 방법으로 비모수적방법, 최대가능도법, 일반화추축량에 의한 방법, 붓스트랩방법의 4가지를 포함확률(coverage probability), 기대길이 (expected length) 측면에서 모의실험을 통하여 비교하였다.

• Journal of applied mathematics & informatics
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• 제25권1_2호
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• pp.435-443
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• 2007

Computing the interior spectrum of large sparse generalized eigenvalue problems $Ax\;=\;{\lambda}Bx$, where A and b are large sparse and SPD(Symmetric Positive Definite), is often required in areas such as structural mechanics and quantum chemistry, to name a few. Recently, CG-type methods have been found useful and hence, very amenable to parallel computation for very large problems. Also, as in the case of linear systems proper choice of preconditioning is known to accelerate the rate of convergence. After the smallest eigenpair is found we use the orthogonal deflation technique to find the next m-1 eigenvalues, which is also suitable for parallelization. This offers advantages over Jacobi-Davidson methods with partial shifts, which requires re-computation of preconditioner matrx with new shifts. We consider as preconditioners Incomplete LU(ILU)(0) in two variants, ever-relaxation(SOR), and Point-symmetric SOR(SSOR). We set m to be 5. We conducted our experiments on matrices from discretizations of partial differential equations by finite difference method. The generated matrices has dimensions up to 4 million and total number of processors are 32. MPI(Message Passing Interface) library was used for interprocessor communications. Our results show that in general the Multi-Color ILU(0) gives the best performance.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제4권2호
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• pp.41-57
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• 2000

In this paper, we consider first order generalized difference scheme for the two-point boundary value problem and one-dimensional second order parabolic type problem. The optimal error estimates in $L_p$ and $W^{1,p}$ ($2{\leq}p{\leq}{\infty}$) as well as some superconvergence estimates in $W^{1,p}$ ($2{\leq}p{\leq}{\infty}$) are obtained. The main results in this paper perfect the theory of GDM.