• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권4호
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• pp.1441-1456
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• 2015

The bidimensional empirical mode decomposition (BEMD) algorithm with high adaptability is more suitable to process multiple image fusion than traditional image fusion. However, the advantages of this algorithm are limited by the end effects problem, multiscale integration problem and number difference of intrinsic mode functions in multiple images decomposition. This study proposes the multiscale self-coordination BEMD algorithm to solve this problem. This algorithm outside extending the feather information with the support vector machine which has a high degree of generalization, then it also overcomes the BEMD end effects problem with conventional mirror extension methods of data processing,. The coordination of the extreme value point of the source image helps solve the problem of multiscale information fusion. Results show that the proposed method is better than the wavelet and NSCT method in retaining the characteristics of the source image information and the details of the mutation information inherited from the source image and in significantly improving the signal-to-noise ratio.

• 산업공학
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• 제1권1호
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• pp.1-7
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• 1988

This paper discusses the applicability of the decomposition principle to an LP (Linear Programming) problem. Through a case study on product mix problems in a chemical process of Korean Steel Chemical Co., Ltd., the decomposition algorithm, LP Simplex method and a modified method are compared and evaluated in computation time and number of iterations.

• 대한수학회논문집
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• 제16권3호
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• pp.487-508
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• 2001

We consider the Cauchy problem for Laplacian. Using the single layer representation, we obtain an equivalent system of boundary integral equations. We show the singular values of the ill-posed Cauchy operator decay exponentially, which means that a small error is exponentially amplified in the solution of the Cauchy problem. We show the decaying rate is dependent on the geometry of he domain, which provides the information on the choice of numerically meaningful modes. We suggest a pseudo-inverse regularization method based on singular value decomposition and present various numerical simulations.

• Smart Structures and Systems
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• 제22권5호
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• pp.621-630
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• 2018

Boundary effect and the noise robustness are the two crucial aspects which affect the effectiveness of the damage localization based on the mode shape measurements. To overcome the boundary effect problem and enhance the noise robustness in damage detection, a simple damage localization method is proposed based on the Singular Value Decomposition (SVD) for the mode shape of composite plates. In the proposed method, the boundary effect problem is addressed by the decomposition and reconstruction of mode shape, and the noise robustness in enhanced by the noise filtering during the decomposition and reconstruction process. Numerical validations are performed on plate-like structures for various damage and boundary scenarios. Validations show that the proposed method is accurate and effective in the damage detection for the two-dimensional structures.

• 한국산학기술학회논문지
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• 제12권8호
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• pp.3384-3390
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• 2011

본 논문은 탄소성 구조해석을 위한 병렬유한요소해석에 필요한 영역분할법에 대해 제시하고 있다. 유한요소해석을 위한 알고리즘으로서 CG방법과 결합한 영역분할법을 이용하였다. 적용된 영역분할법은 탄소성문제를 해석하는데 직접적으로 사용되어 지며 효용성 검토를 위해 3차원 탄소성 구조문제에 적용하여 해석해 본 결과 높은 병렬효과를 발휘함을 알 수 있었다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 추계학술대회논문집A
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• pp.818-823
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• 2000

In practical design studies, most of designers solve multidisciplinary problems with complex design structure. These multidisciplinary problems have hundreds of analysis and thousands of variables. The sequence of process to solve these problems affects the speed of total design cycle. Thus it is very important for designer to reorder original design processes to minimize total cost and time. This is accomplished by decomposing large multidisciplinary problem into several multidisciplinary analysis subsystem (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problem to raise design efficiency by using genetic algorithm and shows the relationship between decomposition and multidisciplinary design optimization (MDO) methodology.

• 한국경영과학회지
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• 제10권1호
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• pp.9-13
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• 1985

This paper develops a decomposition method for stochastic programming with a block diagonal structure. Here we assume that the right-hand side random vector of each subproblem is differente each other. We first, transform this problem into a master problem, and subproblems in a similar way to Dantizig-Wolfe's Decomposition Princeple, and then solve this master problem by solving subproblems. When we solve a subproblem, we first transform this subproblem to a Deterministic Equivalent Programming (DEF). The form of DEF depends on the type of the random vector of the subproblem. We found the subproblem with finite discrete random vector can be transformed into alinear programming, that with continuous random vector into a convex quadratic programming, and that with random vector of unknown distribution and known mean and variance into a convex nonlinear programming, but the master problem is always a linear programming.

• 대한산업공학회지
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• 제40권2호
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• pp.184-194
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• 2014

Numerous studies have been studied to provide an efficient solution for the Nurse Rostering Problem (NRP), most of which have suffered from its complexity arising from incorporating nurse's work shift and ability. The test-bed data for the NRP is released for the public Competition in 2010. This study suggests a new mixed integer programming for Nurse Rostering Problem and develops a hybrid approach, where a hierarchical decomposition and the corresponding optimization are combined. The computation experiment is performed to show that the suggested algorithms may give a better solution in various instances, compared to the one appeared in the literature.

• 스마트미디어저널
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• 제8권2호
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• pp.74-79
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• 2019

기존의 복합명사 분해 알고리즘은 미등록어 단위명사들이 포함된 복합명사를 분해할 때 미등록어를 분리하기 어려운 문제가 발생한다. 이는 현실적으로 모든 고유명사, 신조어, 외래어 등의 모든 단위 명사를 사전에 등록하는 것은 불가능하다는 한계가 존재하기 때문이다. 이 문제를 해결하기 위하여 복합명사 분해 문제를 태그 열 부착(sequence labeling) 문제로 정의하고 음절 단위 임베딩과 딥러닝 기법을 이용하는 복합명사 분해 방법을 제안한다. 단위명사 사전을 구축하지 않고 미등록 단위명사를 인식하기 위하여 복합명사를 구성하는 각 음절들을 연속적인 벡터 공간에 표현하여 LSTM과 선형체인(linear-chain) CRF를 이용하는 방식으로 복합명사를 단위명사들로 분해한다.

• 한국정보과학회논문지:시스템및이론
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• 제34권5_6호
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• pp.195-201
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• 2007

트리의 최소단말경로분할이란 트리를 에지가 서로 소인 단말 노드 간 경로들로 분할하되, 가장 긴 경로의 길이를 최소화하는 문제이다. 본 논문에서는 트리의 최소단말경로분할을 $O({\mid}V{\mid}^2$시간에 구하는 알고리즘을 제시한다. 이 알고리즘은 주어진 최적화 문제를 이에 대응하는 결정 문제, 즉 최소단말경로 분할의 비용이 l 이하인지를 결정하는 문제를 이용한 이진 탐색으로 환원한다. 결정 문제는 트리를 한 차례 순회하는 동안 동적 계획법에 의해 해결된다