• Architectural research
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• 제17권1호
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• pp.31-40
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• 2015

A simple force-finding process based on an optimization technique is proposed for tensegrity structures. For this purpose, the inverse problem of form-finding process is formulated. Therefore, the position vector of nodes and element connectivity information are provided as priori. Several benchmark tests are carried out to demonstrate the performance of the present force-finding process. In particular, the force density distributions of simplex tensegrity are thoroughly investigated with the important parameters such as the radius, height and twisting angle of simplex tensegrity. Finally, the force density distribution of arch tensegrity is produced by using the present force-finding process for a future reference solution.

• 대한전기학회논문지
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• 제43권6호
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• pp.1020-1026
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• 1994

This paper presents a technique to optimize the shape of waveguide components in H-plane. The technique utilizes the numerical optimization process which employs the vector finite element method. In the optimization process, the sensitivity of an objective function with respect to design variables is computed by introducting adjoint variables, which makes the computation easy. The steepest descent method is then employed to update design variables. As a numerical example, an H-plane waveguide teejunction was considered to obtain optimized shape. Comparison between the initial and optimized shape was made.

• Journal of information and communication convergence engineering
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• 제8권4호
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• pp.370-376
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. However, its performance can be degraded due to multicollinearity problem where multiple classifiers of an ensemble are highly correlated with. This paper proposes genetic algorithm-based optimization techniques of SVM ensemble to solve multicollinearity problem. Empirical results with bankruptcy prediction on Korea firms indicate that the proposed optimization techniques can improve the performance of SVM ensemble.

• 동력기계공학회지
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• 제17권5호
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• pp.86-93
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• 2013

This paper proposes the used of genetic algorithm for optimizing PI controller and describes the dynamic modeling simulation for the permanent magnet synchronous motor driven by simplified vector control with the aid of MATLAB-Simulink environment. Furthermore, three kinds of error criterion minimization, integral absolute error, integral square error, and integral time absolute error, are used as objective function in the genetic algorithm. The modeling procedures and simulation results are described and presented in this paper. Computer simulation results indicate that the genetic algorithm was able to optimize the PI controller and gives good control performance of the system. Moreover, simplified vector control on permanent magnet synchronous motor does not need to regulate the direct axis component current. This makes simplified vector control of the permanent magnet synchronous motor very useful for some special applications that need simple control structure and low cost performance.

• Korean Chemical Engineering Research
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• 제48권6호
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• pp.717-724
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• 2010

액체의 화재 및 폭발위험을 나타내는 가장 중요한 물성의 하나인 인화점의 실험 데이터는 그 필요에도 불구하고 실제로 데이터를 확보하는 것이 가능하지 않은 경우가 많다. 이 연구에서는 DIPPR 801에서 얻은 893개 유기물의 인화점 실험데이터로부터 인화점을 예측하는 부분최소자승법(PLS) 및 support vector machine(SVM) 모델을 만들고 비교하였다. 분자를 구성하는 각 구성요소들이 분자의 물성에 일정한 기여를 한다는 가정을 이용하여 분자의 물성을 예측하는 방법인 그룹기여법을 이용하여 65개 작용기가 이 예측모델의 독립변수가 되었고 분자량의 로그값이 추가되었다. 두 모델에서 결정해야 할 매개변수는 교차검증에서 계산된 오차를 이용하여 결정되었는데, SVM모델은 그 매개변수가 많아 particle swarm optimization을 이용한 최적화를 이용하였다. 훈련데이터의 선택이 예측성능에 영향을 줄 수 있어 임의로 100개의 데이터 세트를 생성하여 테스트하였다. 전체 데이터에 대해 계산된 평균절대오차는 PLS가 13.86~14.55였고, SVM이 7.44~10.26여서 SVM이 PLS에 비해 매우 우수한 예측성능을 보였다.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권6호
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• pp.1418-1432
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• 2013

This paper studies the problem of secure information exchange between two sources via multiple relays in the presence of an eavesdropper. To this end, we propose a relay beamforming scheme, i.e., relay beamforming with artificial noise (RBwA), where the relay beamforming vector and the artificial noise vector are jointly designed to maintain the received signal-to-interference-ratio (SINR) at the two sources over a predefined Quality of Service (QoS) threshold while limiting the received SINR at the eavesdropper under a predefined secure threshold. For comparison, the relay beamforming without artificial noise (RBoA) is also considered. We formulate two optimization problems for the two schemes, where our goal is to seek the optimal beamforming vector to minimize the total power consumed by relay nodes such that the secrecy of the information exchange between the two sources can be protected. Since both optimization problems are nonconvex, we solve them by semidefinite program (SDP) relaxation theory. Simulation results show that, via beamforming design, physical layer secrecy of two-way relay networks can be greatly improved and our proposed RBwA outperforms the RBoA in terms of both low power consumption and low infeasibility rate.

• Structural Engineering and Mechanics
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• 제62권6호
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• pp.709-717
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• 2017

This paper develops a two-stage method for structural damage identification by using modal data. First, the Residual Force Vector (RFV) is introduced to detect any potentially damaged elements of structures. Second, data of the frequency domain are used to build up the objective function, and then the Imperialist Competitive Algorithm (ICA) is utilized to estimate damaged extents. ICA is a heuristic algorithm with simple structure, which is easy to be implemented and it is effective to deal with high-dimension nonlinear optimization problem. The advantages of this present method are: (1) Calculation complexity can be decreased greatly after eliminating many intact elements in the first step. (2) Robustness, ICA ensures the robustness of the proposed method. Various damaged cases and different structures are investigated in numerical simulations. From these results, anyone can point out that the present algorithm is effective and robust for structural damage identification and is also better than many other heuristic algorithms.

• 전기전자학회논문지
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• 제23권4호
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• pp.1400-1407
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• 2019

본 논문은 실시간 자가학습과 분류 기능을 모두 지원하는 support vector machine (SVM) 기반 가스 분류기의 하드웨어 구조 설계 및 구현 결과를 제시한다. 제안된 가스 분류기는 학습 알고리즘으로 modified sequential minimal optimization(MSMO)을 사용하였고, 학습과 분류 기능을 공유구조를 사용하여 설계함으로써 기존 논문 대비 하드웨어 면적을 35% 감소시켰다. 설계된 가스 분류기는 Xilinx Zynq UltraScale+ FPGA를 사용하여 구현 및 검증되었고, 108MHz의 동작 주파수에서 3,337개의 CLB LUTs로 구현 가능함을 확인하였다.

• Steel and Composite Structures
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• 제25권4호
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• pp.485-496
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• 2017

In this paper, damage detection has been introduced as an optimization problem and a two-step method has been proposed that can detect the location and severity of damage in truss structures precisely and reduce the volume of computations considerably. In the first step, using the residual force vector concept, the suspected damaged members are detected which will result in a reduction in the number of variables and hence a decrease in the search space dimensions. In the second step, the precise location and severity of damage in the members are identified using the genetic algorithm and the results of the first step. Considering the reduced search space, the algorithm can find the optimal points (i.e. the solution for the damage detection problem) with less computation cost. In this step, the Efficient Correlation Based Index (ECBI), that considers the structure's first few frequencies in both damaged and healthy states, is used as the objective function and some examples have been provided to check the efficiency of the proposed method; results have shown that the method is innovatively capable of detecting damage in truss structures.