• Journal of applied mathematics & informatics
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• 제16권1_2호
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• pp.307-321
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• 2004

In this paper, the unsteady Stokes problem is considered and also the pressure-correction method for the problem is described. At a fixed time level, we reduce the problem to two symmetric positive definite problems which depend on a time step parameter. Linear systems that arise from the problems are large, sparse, symmetric, positive definite and ill-conditioned as the time step tends to zero. Preconditioned problems based on an additive Schwarz method for solving the symmetric positive definite problems are derived and preconditioners are defined implicitly. It will be shown that the rate of convergence is independent of the mesh parameters as well as the time step size.

• 산업경영시스템학회지
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• 제20권44호
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• pp.93-101
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• 1997

This paper describes the application of Genetic Algorithms(GAs) to nonlinear constrained mixed optimization problems. Genetic Algorithms are combinatorial in nature, and therefore are computationally suitable for treating discrete and integer design variables. But, several problems that conventional GAs are ill defined are application of penalty function that can be adapted to transform a constrained optimization problem into an unconstrained one and premature convergence of solution. Thus, we developed an improved GAs to solve this problems, and two examples are given to demonstrate the effectiveness of the methodology developed in this paper.

• Journal of Electrical Engineering and Technology
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• 제4권2호
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• pp.149-158
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• 2009

It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.825-835
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• 2017

Significant improvements to methodologies on structural damage detection (SDD) have emerged in recent years. However, many methods are related to inversion computation which is prone to be ill-posed or ill-conditioning, leading to low-computing efficiency or inaccurate results. To explore a more accurate solution with satisfactory efficiency, a PSO-INM algorithm, combining particle swarm optimization (PSO) algorithm and an improved Nelder-Mead method (INM), is proposed to solve multi-sample objective function defined based on Bayesian inference in this study. The PSO-based algorithm, as a heuristic algorithm, is reliable to explore solution to SDD problem converted into a constrained optimization problem in mathematics. And the multi-sample objective function provides a stable pattern under different level of noise. Advantages of multi-sample objective function and its superior over traditional objective function are studied. Numerical simulation results of a two-storey frame structure show that the proposed method is sensitive to multi-damage cases. For further confirming accuracy of the proposed method, the ASCE 4-storey benchmark frame structure subjected to single and multiple damage cases is employed. Different kinds of modal identification methods are utilized to extract structural modal data from noise-contaminating acceleration responses. The illustrated results show that the proposed method is efficient to exact locations and extents of induced damages in structures.

• 한국정보통신학회논문지
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• 제19권3호
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• pp.645-650
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• 2015

영상 획득 시 렌즈의 부정확한 초점이나 영상 획득 시스템의 흔들림 등으로 인해 영상 복원이 요구된다. 이런 영상 복원 문제는 하나의 열화 영상에서 원 영상을 추출해야 하는 부적절하게 정립된 역 문제 (ill-posed reverse problem)이다. 본 논문은 기준 영상을 도입하여 기존의 영상 복원 방법과 비교할 때 복원 영상의 신호잡음비를 유사하게 유지하면서 계산 속도를 향상시키는 방법을 제안하였다. 제안된 방법은 새로운 비용 함수를 통해 영상과 커널을 몇 단계의 갱신을 통해 영상 열화에 사용되었다고 추정되는 커널을 얻는다. 위너 필터는 전 단계에서 구한 커널과 기준 영상을 이용하여 원 영상의 추정치를 구하였다.

• 디지털콘텐츠학회 논문지
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• 제5권4호
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• pp.289-294
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• 2004

영상분석을 하기 위하여 이용되는 많은 방법들은 기본적으로 잘 알려진 여러 가지 수학적인 이론에 기초해 전개 된다. 예로써 영상을 이변 함수에 대응시켜 기존의 미분 또는 편미분을 통한 경도 및 에너지 함수를 이용하거나 미분기하학적 측면에서 접평면 및 곡률을 사용하는 등과 같이 전통의 수학적 기법댐들이 적용되기도 한다. 그러나 국소적 변화를 효과적으로 분석하기 위해 사용되는 이러한 수학적 이론은 대상을 표현하는 함수가 충분히 연속적으로 변화하는 매우 부드러운 함수임을 가정하는 데에서 시작하게 된다. 그러므로 실제 자연의 형상 또는 현상을 구현하는 함수에 알려진 수학적 이론을 직접적으로 대입하므로 야기되는 여러 가지 불량문제를 종종 접하게 된다. 이러한 문제를 해결하기 위한 한 방법으로 본 논문에서는 보다 효율적으로 계산되고 광범위하게 적용될 수 있는 약미분을 정의하고 이를 해석하고자 하였다.

• 한국수학교육학회지시리즈A:수학교육
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• 제57권2호
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• pp.111-136
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• 2018

This study suggests a framework for analyzing items based on the characteristics, and shows the relationship among the characteristics, difficulty, percentage of correct answers, academic achievement and the actual mathematical problem solving competency. Three mathematics educators' classification of 30 items of Mathematics 'Ga' type, on 2017 College Scholastic Ability Test, and the responses given by 148 high school students on the survey examining mathematical problem solving competency were statistically analyzed. The results show that there are only few items satisfying the characteristics for mathematical problem solving competency, and students feel ill-defined and non-routine items difficult, but in actual percentage of correct answers, routineness alone has an effect. For the items satisfying the characteristics, low-achieving group has difficulty in understanding problem, and low and intermediate-achieving group have difficulty in mathematical modelling. The findings can suggest criteria for mathematics teachers to use when developing mathematics questions evaluating problem solving competency.

• 경영과정보연구
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• 제2권
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• pp.169-193
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• 1998

Case- based reasoning(CBR) offers a new approach for developing knowledge based systems. Unlike the rule-based paradigm, in which domain knowledge is encoded in the form of production rules, in the case-based approach the problem solving experience of the domain expert is encoded in the form of cases stored in a casebase(CB). CBR allows a reasoner (1) to propose solutions in domains that are not completely understood by the reasoner, (2) to evaluate solutions when no algorithmic method is available for evaluation, and (3) to interprete open-ended and ill-defined concepts. CBR also helps reasoner (4) take actions to avoid repeating past mistakes, and (5) focus its reasoning on important parts of a problem. Owing to the above advantages, CBR has successfully been applied to many kinds of problems such as design, planning, diagnosis and instruction. In this paper, I propose case-based DSS(CBDSS). CBDSS is an intelligent DSS using CBR technique. CBDSS consists of interface, case-based reasoner, maintainer, casebase management system, domain dependent CB, domain independent CB, and so on.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.519-524
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• 1996

This paper describes the application of Genetic Algorithms(GAs) to nonlinear constrained mixed optimization problems. Genetic Algorithms are combinatorial in nature, and therefore are computationally suitable for treating discrete and integer design variables. But, several problems that conventional GAs are ill defined are applicaiton of penalty function that can be adapted to transform a constrained optimization problem into an unconstrained optimization problem into an unconstrained one and premature convergence of solution. Thus, we developed an modified GAs to solve this problems, and two examples are given to demonstrate the effectiveness of the methodology developed in this paper.

• 대한산업공학회지
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• 제23권1호
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• pp.39-54
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• 1997

This paper presents four process models for machining processes : 1) an economical mathematical model of machining process, 2) a prediction model for surface roughness, 3) a decision model for fuzzy cutting conditions, and 4) a judgment model of machinability with automatic selection of cutting conditions. Each model was developed the economic machining, and these models were applied to theories widely studied in industrial engineering which are nonlinear programming, computer simulation, fuzzy theory, and neural networks. The results of this paper emphasize the human oriented domain of a nonlinear programming problem. From a viewpoint of the decision maker, fuzzy nonlinear programming modeling seems to be apparently more flexible, more acceptable, and more reliable for uncertain, ill-defined, and vague problem situations.