• Journal of applied mathematics & informatics
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• v.39 no.3_4
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• pp.587-600
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• 2021

Some problems in engineering and science can be equivalently transformed into solving multi-linear systems. In this paper, we propose two preconditioned AOR iteration methods to solve multi-linear systems with -tensor. Based on these methods, the general conditions of preconditioners are given. We give the convergence theorem and comparison theorem of the two methods. The results of numerical examples show that methods we propose are more effective.

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.26 no.1
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• pp.1-14
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• 1998

Various numerical methods for the two dimensional shallow water equations have been applied to the problems of flood routing, tidal circulation, storm surges, and atmospheric circulation. These methods are often based on the Alternating Direction Implicity(ADI) method. However, the ADI method results in inaccuracies for large time steps when dealing with a complex geometry or bathymetry. Since this method reduces the performance considerably, a fully implicit method developed by Wilders et al. (1998) is used to improve the accuracy for a large time step. Finite Difference Methods are defined on a rectangular grid. Two drawbacks of this type of grid are that grid refinement is not possibile locally and that the physical boundary is sometimes poorly represented by the numerical model boundary. Because of the second deficiency several purely numerical boundary effects can be involved. A boundary fitted curvilinear coordinate transformation is used to reduce these difficulties. It the curvilinear coordinate transformation is used to reduce these difficulties. If the coordinate transformation is orthogonal then the transformed shallow water equations are similar to the original equations. Therefore, an orthogonal coorinate transformation is used for defining coordinate system. A multigrid (MG) method is widely used to accelerate the convergence in the numerical methods. In this study, a technique using a MG method is proposed to reduce the computing time and to improve the accuracy for the orthogonal to reduce the computing time and to improve the accuracy for the orthogonal grid generation and the solutions of the shallow water equations.

• Communications of the Korean Mathematical Society
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• v.34 no.2
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• pp.657-670
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• 2019

In this paper, we consider the preconditioned iterative methods for solving linear complementarity problem associated with an M-matrix. Based on the generalized Gunawardena's preconditioner, two preconditioned SSOR methods for solving the linear complementarity problem are proposed. The convergence of the proposed methods are analyzed, and the comparison results are derived. The comparison results showed that preconditioned SSOR methods accelerate the convergent rate of the original SSOR method. Numerical examples are used to illustrate the theoretical results.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.4
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• pp.162-172
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• 2021

This paper proposes stochastic methods to find an approximate solution for the L²-Wasserstein least squares problem of Gaussian measures. The variable for the problem is in a set of positive definite matrices. The first proposed stochastic method is a type of classical stochastic gradient methods combined with projection and the second one is a type of variance reduced methods with projection. Their global convergence are analyzed by using the framework of proximal stochastic gradient methods. The convergence of the classical stochastic gradient method combined with projection is established by using diminishing learning rate rule in which the learning rate decreases as the epoch increases but that of the variance reduced method with projection can be established by using constant learning rate. The numerical results show that the present algorithms with a proper learning rate outperforms a gradient projection method.

• 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.

• Communications of the Korean Mathematical Society
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• v.13 no.1
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• pp.195-209
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• 1998

In this paper we present a new iteration method for solving optimization problems governed by partial differential equations. We generalize the existing methods such as simple gradient methods and pseudo-time methods to get an efficient iteration method. Numerical tests show that the convergence of the new iteration method is much faster than those of the pseudo-time methods especially when the parameter $\sigma$ in the cost functional is small.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.169.4-169
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• 2001

Conventional methods to solve the nonlinear programming problem range from augmented Lagrangian methods to sequential quadratic programming (SQP) methods. NPSOL, which is a SQP code, has been widely used to solve various optimization problems but is still subject to many numerical problems such as convergence to local optima, difficulties in initialization and in handling non-smooth cost functions. Recently, many evolutionary methods have been developed for constrained optimization. Among them, CEALM (Co-Evolutionary Augmented Lagrangian Method) shows excellent performance in the following aspects: global optimization capability, low sensitivity to the initial parameter guessing, and excellent constraint handling capability due to the benefit of the augmented Lagrangian function. This algorithm is ...

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.3
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• pp.21-26
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• 2009

The finite element analysis of metal forming processes often fails because of severe mesh distortion at large deformation. As the concept of meshless methods, only nodal point data are used for modeling and solving. As the main feature of these methods, the domain of the problem is represented by a set of nodes, and a finite element mesh is unnecessary. This computational methods reduces time-consuming model generation and refinement effort. It provides a higher rate of convergence than the conventional finite element methods. The displacement shape functions are constructed by the reproducing kernel approximation that satisfies consistency conditions. In this research, A meshless method approach based on the reproducing kernel particle method (RKPM) is applied with metal forming analysis. Numerical examples are analyzed to verify the performance of meshless method for metal forming analysis.

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.273-280
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• 2007

The numerical methods for finding the optimal parameters in 640 Gbps (16 channels $\times$ 40 Gbps) WDM system with optical phase conjugator (OPC) are proposed, which effectively compensate the distorted overall WDM channels. The considered optimal parameters are the OPC position and the dispersion coefficient of fibers. The numerical approaches are accomplished through two different procedures. One of these procedures is that the optimal OPC position is previously searched and then the optimal dispersion coefficient is searched at the obtained optimal OPC position. The other is the reverse of the above procedure. From the numerical results, it is confirmed that two optimal parameters depend on each other, but less related with the searching procedure. The methods proposed in this research will be expected to alternate with the method of making a symmetrical distribution of power and local dispersion in real optical link which is a serious problem of applying the OPC into multi-channels WDM system.

• Journal of the Korean Mathematical Society
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• v.57 no.5
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• pp.1239-1266
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• 2020

In this paper, some novel discrete formulations for stabilizing the mixed finite element method Q1-Q0 (bilinear velocity and constant pressure approximations) are introduced and discussed for the generalized Stokes problem. These are based on stabilizing discontinuous pressure approximations via local jump operators. The developing idea consists in a reduction of terms in the local jump formulation, introduced earlier, in such a way that stability and convergence properties are preserved. The computer implementation aspects and numerical evaluation of these stabilized discrete formulations are also considered. For illustrating the numerical performance of the proposed approaches and comparing the three versions of the local jump methods alongside with the global jump setting, some obtained results for two test generalized Stokes problems are presented. Numerical tests confirm the stability and accuracy characteristics of the resulting approximations.