• Communications of the Korean Mathematical Society
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• v.25 no.2
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• pp.207-214
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• 2010

In this paper, a generalized variational inequality problem is considered. An iterative method is studied for approximating a solution of the generalized variational inequality problem. Strong convergence theorem are established in a real Hilbert space.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.444-447
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• 2004

A new approach to compute the control moves in Extended Dynamic Matrix Control (EDMC) is presented. In this approach, the number of variables, determined in the inner loop of the control algorithm using iterative methods, is reduced from P , the prediction horizon to M , the control horizon. Since M is usually much smaller than P , this modifies the control algorithm from computational point of view. To justify the modification, the computational requirements are compared to those of the existing EDMC algorithm.

• Journal of applied mathematics & informatics
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• v.31 no.5_6
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• pp.733-745
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• 2013

In this paper, we first propose a new technique of the functional iterative methods VIM (Variational iteration method) and NHPM (New homotopy perturbation method) for solving two-point boundary value problems, and then we compare their numerical results with those of the finite difference method (FDM).

• Bulletin of the Korean Mathematical Society
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• v.54 no.4
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• pp.1347-1359
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• 2017

The purpose of this paper is to give some new iterative methods for finding a common zero of a finite family of monotone operators in Hilbert spaces. We also give the applications of the obtained result for the convex feasibility problem and constrained convex optimization problem in Hilbert spaces.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.734-739
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• 1988

For the trajectory control of dynamic systems with unidentified parameters a second-order iterative learning control method is presented. In contrast to other known methods, the proposed learning control scheme can utilize more than one error history contained in the trajectories generated at prior iterations. A convergency proof is given and it is also shown that the convergence speed can be improved in compared to conventional methods. Examples are provided to show effectiveness of the algorithm, and, via simulation, it is demonstrated that the method yields a good performance even in the presence of distubances.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.1319-1330
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• 2009

In [2] A.Hadjidimos proposed the generalized accelerated over-relaxation (GAOR) methods which generalize the basic iterative method for the solution of linear systems. In this paper we consider the convergence of the two parallel accelerated generalized AOR iterative methods and obtain some convergence theorems for the case when the coefficient matrix A is a block diagonally dominant matrix or a generalized block diagonally dominant matrix.

• Communications of the Korean Mathematical Society
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• v.9 no.2
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• pp.449-465
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• 1994

The two common numerical methods to approximate the solution of partial differential equations are the finite element method and the finite difference method. They both lead to solving large sparse linear systems. For many applications, it is not unusal that the order of matrix is greater than 10, 000. For this kind of problem, a direct method such as Gaussian elimination can not be used because of the prohibitive cost. To this end, many iterative methods with modest cost have been studied and proposed by numerical analysts.(omitted)

• Coupled systems mechanics
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• v.4 no.3
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• pp.263-277
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• 2015

This paper presents a coupled FEM-BEM strategy for the numerical analysis of elastodynamic problems where infinite-domain models and complex heterogeneous media are involved, rendering a configuration in which neither the Finite Element Method (FEM) nor the Boundary Element Method (BEM) is most appropriate for the numerical analysis. In this case, the coupling of these methodologies is recommended, allowing exploring their respective advantages. Here, frequency domain analyses are focused and an iterative FEM-BEM coupling technique is considered. In this iterative coupling, each sub-domain of the model is solved separately, and the variables at the common interfaces are iteratively updated, until convergence is achieved. A relaxation parameter is introduced into the coupling algorithm and an expression for its optimal value is deduced. The iterative FEM-BEM coupling technique allows independent discretizations to be efficiently employed for both finite and boundary element methods, without any requirement of matching nodes at the common interfaces. In addition, it leads to smaller and better-conditioned systems of equations (different solvers, suitable for each sub-domain, may be employed), which do not need to be treated (inverted, triangularized etc.) at each iterative step, providing an accurate and efficient methodology.

• Structural Engineering and Mechanics
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• v.36 no.5
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• pp.529-544
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• 2010

Nonlinear equations of structures are generally solved numerically by the iterative solution of linear equations. However, this iterative procedure diverges when the tangent stiffness is ill-conditioned which occurs near limit points. In other words, a major challenge with simple iterative methods is failure caused by a singular or near singular Jacobian matrix. In this paper, using the Newton-Raphson algorithm based on Davidenko's equations, the iterations can traverse the limit point without difficulty. It is argued that the propose algorithm may be both more computationally efficient and more robust compared to the other algorithm when tracing path through severe nonlinearities such as those associated with structural collapse. Two frames are analyzed using the proposed algorithm and the results are compared with the previous methods. The ability of the proposed method, particularly for tracing the limit points, is demonstrated by those numerical examples.

• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.205-215
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• 2021

Sufficient dimension reduction is useful dimension reduction tool in regression, and sliced inverse regression (Li, 1991) is one of the most popular sufficient dimension reduction methodologies. In spite of its popularity, it is known to be sensitive to the number of slices. To overcome this shortcoming, the so-called fused sliced inverse regression is proposed by Cook and Zhang (2014). Unfortunately, the two existing methods do not have the direction application to large p-small n regression, in which the dimension reduction is desperately needed. In this paper, we newly propose seeded sliced inverse regression and seeded fused sliced inverse regression to overcome this deficit by adopting iterative projection approach (Cook et al., 2007). Numerical studies are presented to study their asymptotic estimation behaviors, and real data analysis confirms their practical usefulness in high-dimensional data analysis.