• Steel and Composite Structures
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• 제37권6호
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• pp.663-678
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• 2020

This paper proposes a novel topology optimization method generating multiple materials for external linear plane crack structures based on the combination of IsoGeometric Analysis (IGA) and eXtended Finite Element Method (X-FEM). A so-called eXtended IsoGeometric Analysis (X-IGA) is derived for a mechanical description of a strong discontinuity state's continuous boundaries through the inherited special properties of X-FEM. In X-IGA, control points and patches play the same role with nodes and sub-domains in the finite element method. While being similar to X-FEM, enrichment functions are added to finite element approximation without any mesh generation. The geometry of structures based on basic functions of Non-Uniform Rational B-Splines (NURBS) provides accurate and reliable results. Moreover, the basis function to define the geometry becomes a systematic p-refinement to control the field approximation order without altering the geometry or its parameterization. The accuracy of analytical solutions of X-IGA for the crack problem, which is superior to a conventional X-FEM, guarantees the reliability of the optimal multi-material retrofitting against external cracks through using topology optimization. Topology optimization is applied to the minimal compliance design of two-dimensional plane linear cracked structures retrofitted by multiple distinct materials to prevent the propagation of the present crack pattern. The alternating active-phase algorithm with optimality criteria-based algorithms is employed to update design variables of element densities. Numerical results under different lengths, positions, and angles of given cracks verify the proposed method's efficiency and feasibility in using X-IGA compared to a conventional X-FEM.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.57-62
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• 2005

Microarray gene expression profiling technology is one of the most important research topics in clinical diagnosis of disease. Given thousands of genes, only a small number of them show strong correlation with a certain phenotype. To identify such an optimal subset from thousands of genes is intractable, which plays a crucial role when classify multiple-class genes express models from tumor samples. This paper proposes an efficient classifier design method to simultaneously select the most relevant genes using an intelligent genetic algorithm (IGA) and design an accurate classifier using Support Vector Machine (SVM). IGA with an intelligent crossover operation based on orthogonal experimental design can efficiently solve large-scale parameter optimization problems. Therefore, the parameters of SVM as well as the binary parameters for gene selection are all encoded in a chromosome to achieve simultaneous optimization of gene selection and the associated SVM for accurate tumor classification. The effectiveness of the proposed method IGA/SVM is evaluated using four benchmark datasets. It is shown by computer simulation that IGA/SVM performs better than the existing method in terms of classification accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.120.1-120
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• 2002

In this paper, we propose an interactive genetic algorithm (IGA) to implement an automated 2D avatar synthesis. The IGA technique is capable of expressing user's personality in the avatar synthesis by using the user's response as a candidate for the fitness value. Our suggested IGA method isapplied to creating avatars automatically. Unlike the previous works, we introduce the concepts of 'hidden population', as well as 'primitive avatar' and 'simplified genotype', which are used to overcome the shortcomings of IGA such as human fatigue or reliability, and reasonable rates of convergence with a less number of iterations. The procedure of designing avatar models consists of two steps. The firl...

• 한국전산구조공학회논문집
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• 제31권5호
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• pp.275-282
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• 2018

등기하 해석법을 이용한 고유치 해석은 유한요소를 이용한 결과보다 고차 모드에서 더 정확한 결과를 주는 것으로 알려져 있다. 이는 유한요소법이 차수에 상관없이 요소 간에 $C^0$ 연속성을 보이는 것과 다르게 등기하 해석법은 p차 요소에 대해서 $C^{p-1}$의 연속성을 보장하기 때문이다. 본 논문에서는 이러한 장점을 이용하여 등기하 해석법을 이용하여 모드 기반의 축소 모델을 구성하고 동적 거동 해석을 수행하였다. 축소 모델 구성을 위해 Craig-Bampton(CB) 기법을 적용하였다. 수치 예제를 통해 간단한 봉 요소에 대해 등기하 해석법과 유한요소 해석법을 적용하여 요소의 차수에 따른 고유치 해석 결과를 비교분석하였다. 등기하 해석법에 중첩 노트를 허용하여 요소 간 연속성을 조절하고, 요소 간 연속성이 줄어듦에 따라 고차 모드에서의 수치 오차가 커짐을 확인하였다. 동적 거동 해석을 위한 축소 모델에 높은 차수의 외력이 주어지는 경우 요소간 연속성이 높은 등기하해석법을 사용하면, 해의 정확도를 높일 수 있다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.167-173
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• 2002

In this paper, we propose an interactive genetic algorithm (IGA) to implement an automated 2D avatar synthesis. The IGA technique is capable of expressing user's personality in the avatar synthesis by using the user's response as a candidate for the fitness value. Our suggested IGA method is applied to creating avatars automatically. Unlike the previous works, we introduce the concepts of 'hidden population', as well as 'primitive avatar' and 'simplified genotype', which are used to overcome the shortcomings of IGA such as human fatigue or reliability, and reasonable rates of convergence with a less number of iterations. The procedure of designing avatar models consists of two steps. The first step is to detect the facial feature points and the second step is to create the subjectively optimal avatars with diversity by embedding user's preference, intuition, emotion, psychological aspects, or a more general term, KANSEI. Finally, the combined processes result in human-friendly avatars in terms of both genetic optimality and interactive GUI with reliability.

• Steel and Composite Structures
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• 제21권6호
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• pp.1389-1410
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• 2016

This paper proposes a hybrid of topological derivative-based level set method (LSM) and isogeometric analysis (IGA) for structural topology optimization. In topology optimization a significant drawback of the conventional LSM is that it cannot create new holes in the design domain. In this study, the topological derivative approach is used to create new holes in appropriate places of the design domain, and alleviate the strong dependency of the optimal topology on the initial design. Furthermore, the values of the gradient vector in Hamilton-Jacobi equation in the conventional LSM are replaced with a Delta function. In the topology optimization procedure IGA based on Non-Uniform Rational B-Spline (NURBS) functions is utilized to overcome the drawbacks in the conventional finite element method (FEM) based topology optimization approaches. Several numerical examples are provided to confirm the computational efficiency and robustness of the proposed method in comparison with derivative-based LSM and FEM.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1034-1038
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• 2005

This paper presents a novel method to speed up neural network (NN) based face detection systems. NN-based face detection can be viewed as a classification and search problem. The proposed method formulates the search problem as an integer nonlinear optimization problem (INLP) and develops an improved genetic algorithm (IGA) to solve it. Each individual in the IGA represents a subwindow in an input image. The subwindows are evaluated by how well they match a NN-based face filter. A face is indicated when the filter response of the best particle is above a given threshold. Experimental results show that the proposed method leads to a speedup of 83 on $320{\times}240$ images compared to the traditional exhaustive search method.

• 비파괴검사학회지
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• 제22권2호
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• pp.198-202
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• 2002

가동중인 증기발생기 전열관에서 발생하는 결함 유형 중의 하나인 입계부식은 방전가공에 의한 모의 시편 제작이 불가능하므로 입계부식에 대한 와전류검사 신호의 특성이 잘 알려져 있지 않다. 본 연구에서는 0.1 M sodium tetrathionate 용액에서 비확관 전열관에 입계부식을 형성시키고 와전류검사 신호를 수집하여 평가하였다. 이를 통하여 탐촉자의 종류와 주파수에 따른 선호 특성 및 입계부식의 깊이 변화에 따른 검출능을 비교하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 학술대회 논문집 전문대학교육위원
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• pp.104-106
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• 2000

This paper presents an algorithm for optimal reactive power dispatch problem based on Improved Genetic Algorithm(IGA). Optimal Reactive Power Dispatch (ORPD) is particularized to the minimization of transmission line losses by suitable selection of generator reactive power outputs and transformer tap setting. For the objective, in this paper, Loss Re-Distribution Algorithm(LRDA) is new applied to the equality constraint of ORPD. The proposed method has been evaluated on the IEEE 30 bus system. Results of the application of the method are compared with a base case.

• Structural Engineering and Mechanics
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• 제70권2호
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• pp.209-219
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• 2019

By normalizing the internal hysteresis variable and eliminating the redundant parameter, the normalized Bouc-Wen model is considered to be an improved and more reasonable form of the Bouc-Wen model. In order to facilitate application and further research of the normalized Bouc-Wen model, some key aspects of the model need to be uncovered. In this paper, hysteresis characterization of the normalized Bouc-Wen model is first studied with respect to the model parameters, which reveals the influence of each model parameter to the shape of the hysteresis loops. The parameter identification scheme is then proposed based on an improved genetic algorithm (IGA), and verified by experimental test data. It is proved that the proposed method can be an efficacious tool for identification of the model parameters by matching the reconstructed hysteresis loops with the target hysteresis loops. Meanwhile, the IGA is shown to outperform the standard GA. Finally, a simplified identification method is proposed based on parameter sensitivity, which indicates that the efficiency of the identification process can be greatly enhanced while maintaining comparable accuracy if the low-sensitivity parameters are reasonably restricted to narrower ranges.