• Journal of applied mathematics & informatics
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• 제25권1_2호
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• pp.119-136
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• 2007

Block Jacobi and Gauss-Seidel iterative methods are studied for solving $n{\times}n$ fuzzy linear systems. A new splitting method is considered as well. These methods are accompanied with some convergence theorems. Numerical examples are presented to illustrate the theory.

• 대한수학회논문집
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• 제28권3호
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• pp.603-613
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• 2013

In 2009, Zheng and Miao [B. Zheng and S.-X. Miao, Two new modified Gauss-Seidel methods for linear system with M-matrices, J. Comput. Appl. Math. 233 (2009), 922-930] considered the modified Gauss-Seidel method for solving M-matrix linear system with the preconditioner $P_{max}$. In this paper, we consider the modified Gauss-Seidel method for solving the linear system with the generalized preconditioner $P_{max}({\alpha})$, and study its convergent properties when the coefficient matrix is an H-matrix. Numerical experiments are performed with different examples, and the numerical results verify our theoretical analysis.

• 한국전자파학회논문지
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• 제25권5호
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• pp.601-606
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• 2014

IPO(Iterative Physical Optics) 방법은 대규모 물체의 산란파를 효과적으로 계산하는 고주파 근사 방법 중 하나인 PO(Physical Optics) 방법을 반복적으로 적용하는 계산방법이다. IPO 방법은 일차(first-order) PO 방법에서는 고려하지 못하는 다중 반사를 고려할 수 있어, 산란체 표면에 여기되는 전류의 정확도를 높일 수 있다. 그러므로 산란체의 RCS(Radar Cross Section)를 보다 정확하게 예측할 수 있다. 그러나 IPO 방법은 필요한 적분방정식을 정확하게 풀지 않아 수렴성에 문제가 생긴다. 그러므로 본 논문에서는 IPO 방법의 수렴성을 조절하기 위해, 행렬연산에 사용하는 Jacobi, Gauss-Seidel, SOR(Successive Over Relaxation) 그리고 Richardson 방법을 IPO 방법에 적용하였다. 그러므로 대규모 물체의 RCS 계산을 제안된 IPO 방법을 사용하여 효율적으로 계산할 수 있다. 또, 이들의 정확도를 시뮬레이션을 통해 검증하였다.

• 산업경영시스템학회지
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• 제8권12호
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• pp.127-138
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• 1985

There are several methods which have been presented up to now in solving the simultaneous linear equations by computer. They are Gaussian Elimination Method, Gauss-Jordan Method, Inverse matrix Method and Gauss-Seidel iterative Method. This paper is not only discussed in their mechanisms compared with their algorithms, depicted flow charts, but also calculated the numbers of arithmetic operations and comparisons in order to criticize their availability. Inverse Matrix Method among em is founded out the smallest in the number of arithmetic operation, but is not the shortest operation time. This paper also indicates the many problems in using these methods and propose the new method which is able to applicate to even small or middle size computers.

• Journal of applied mathematics & informatics
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• 제9권1호
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• pp.101-124
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• 2002

The convergence rate of a numerical procedure barred on Schwarz Alternating Method (SAM) for solving elliptic boundary value problems (BVP's) depends on the selection of the interface conditions applied on the interior boundaries of the overlapping subdomains. It hee been observed that the Robin condition(mixed interface condition), controlled by a parameter, can optimize SAM's convergence rate. Since the convergence rate is very sensitive to the parameter, Tang[17] suggested another interface condition called over-determined interface condition. Based on the over-determined interface condition, we formulate the two-layer multi-parameterized SAM. For the SAM and the one-dimensional elliptic model BVP's, we determine analytically the optimal values of the parameters. For the two-dimensional elliptic BVP's , we also formulate the two-layer multi-parameterized SAM and suggest a choice of multi-parameter to produce good convergence rate .

• 산업경영시스템학회지
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• 제40권4호
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• pp.137-146
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• 2017

For the competitive business environment under purchase dependence, this paper proposes a new approximate calculation of order fill rate which is a probability of satisfying a customer order immediately using the existing inventory. Purchase dependence is different to demand dependence. Purchase dependence treats the purchase behavior of customers, while demand dependence considers demand correlation between items, between regions, or over time. Purchase dependence can be observed in such areas as marketing, manufacturing systems, and distribution systems. Traditional computational methods have a difficulty of the curse of dimensionality for the large cases, when deriving the stationary joint distribution which is utilized to calculate the order fill rate. In order to escape the curse of dimensionality and protect the solution from diverging for the large cases, we develop a greedy iterative search algorithm based on the Gauss-Seidel method. We show that the greedy iterative search algorithm is a dependable algorithm to derive the stationary joint distribution of on-hand inventories in the retailer system by conducting a comparison analysis of a greedy iterative search algorithm with the simulation. In addition, we present some managerial insights such as : (1) The upper bound of order fill rate can be calculated by the one-item pure system, while the lower bound can be provided by the pure system that consists of all items; (2) As the degree of purchase dependence declines while other conditions remain same, it is observed that the difference between the lower and upper bounds reduces, the order fill rate increases, and the order fill rate gets closer to the upper bound.