• Earthquakes and Structures
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• 제1권3호
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• pp.289-306
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• 2010

A gradient-based evolutionary optimization methodology is presented for finding the optimal design of viscous dampers to minimize an objective function defined for a linear multi-storey structure. The maximum value along height of the transfer function amplitudes for the interstorey drifts is taken as the objective function. Since the ground motion includes various uncertainties, the optimal damper placement may be different depending on the ground motion used for design. Furthermore, the transfer function treated as the objective function depends on the properties of structural parameters and added dampers. This implies that a more robust damper design is desired. A reliable and robust damping design system against any unpredictable ground motions can be provided by minimizing the maximum transfer function. Such design system is proposed in this paper.

• 제어로봇시스템학회논문지
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• 제7권12호
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• pp.985-992
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• 2001

This paper proposes a self-organizing fuzzy modeling(SOFUM)which an create a new hyperplane shaped cluster and adjust parameters of the fuzzy model in repetition. The suggested algorithm SOFUM is composed of four steps: coarse tuning. fine tuning cluster creation and optimization of learning rates. In the coarse tuning fuzzy C-regression model(FCRM) clustering and weighted recursive least squared (WRLS) algorithm are used and in the fine tuning gradient descent algorithm is used to adjust parameters of the fuzzy model precisely. In the cluster creation, a new hyperplane shaped cluster is created by applying multiple regression to input/output data with relatively large fuzzy entropy based on parameter tunings of fuzzy model. And learning rates are optimized by utilizing meiosis-genetic algorithm in the optimization of learning rates To check the effectiveness of the suggested algorithm two examples are examined and the performance of the identified fuzzy model is demonstrated via computer simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.515-518
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• 1998

This paper proposes a new hybrid algorithm for auto-tuning fuzzy controllers improving the performance. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a genetic-MGM algorithm. The object of the proposed algorithm is to promote search efficiency by a genetic and modified gradient optimization techniques. The proposed genetic and MGM algorithm is based on both the standard genetic algorithm and a gradient method. If a maximum point don't be changed around an optimal value at the end of performance during given generation, the genetic-MGM algorithm searches for an optimal value using the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algorithms. Simulation results verify the validity of the presented method.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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• pp.119-126
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• 2004

A continuum-based design sensitivity analysis and topology optimization methods are developed for power flow analysis. Efficient adjoint sensitivity analysis method is employed and further extended to topology optimization problems. Young's moduli of all the finite elements are selected as design variables and parameterized using a bulk material density function. The objective function and constraint are an energy compliance of the system and an allowable volume fraction, respectively. A gradient-based optimization, the modified method of feasible direction, is used to obtain the optimal material layout. Through several numerical examples, we notice that the developed design sensitivity analysis method is very accurate and efficient compared with the finite difference sensitivity. Also, the topology optimization method provides physically meaningful results. The developed is design sensitivity analysis method is very useful to systematically predict the impact on the design variations. Furthermore, the topology optimization method can be utilized in the layout design of structural systems.

• 설비공학논문집
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• 제16권12호
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• pp.1156-1166
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• 2004

The shape of plate-fin type heat sink is numerically optimized to acquire the minimum pressure drop under the required temperature rise. In constrained nonlinear optimization problems of thermal/fluid systems, three fundamental difficulties such as high computational cost for function evaluations (i.e., pressure drop and thermal resistance), the absence of design sensitivity information, and the occurrence of numerical noise are commonly confronted. Thus, a sequential approximate optimization (SAO) algorithm has been introduced because it is very hard to obtain the optimal solutions of fluid/thermal systems by means of gradient-based optimization techniques. In this study, the progressive quadratic response surface method (PQRSM) based on the trust region algorithm, which is one of sequential approximate optimization algorithms, is used for optimization and the heat sink is optimized by combining it with the computational fluid dynamics (CFD).

• 대한기계학회논문집A
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• 제27권7호
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• pp.1234-1242
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• 2003

In this paper we present a simple and efficient robust optimal design formulation for MEMS structures and its application to a resonant-type micro probe. The basic idea is to use the gradient index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-effective and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation. This method, although shown for MEMS structures, may as well be easily applied to conventional mechanical structures where information on uncertainties is lacking but robustness is highly important.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.448-448
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• 2018

In this study, the regression models (Load ESTimator and eight-parameter model) were evaluated to estimate instantaneous pollutant loads under various criteria and optimization methods. As shown in the results, LOADEST commonly used in interpolating pollutant loads could not necessarily provide the best results with the automatic selected regression model. It is inferred that the various regression models in LOADEST need to be considered to find the best solution based on the characteristics of watersheds applied. The recently developed eight-parameter model integrated with Genetic Algorithm (GA) and Gradient Descent Method (GDM) were also compared with LOADEST indicating that the eight-parameter model performed better than LOADEST, but it showed different behaviors in calibration and validation. The eight-parameter model with GDM could reproduce the nitrogen loads properly outside of calibration period (validation). Furthermore, the accuracy and precision of model estimations were evaluated using various criteria (e.g., $R^2$ and gradient and constant of linear regression line). The results showed higher precisions with the $R^2$ values closed to 1.0 in LOADEST and better accuracy with the constants (in linear regression line) closed to 0.0 in the eight-parameter model with GDM. In hence, based on these finding we recommend that users need to evaluate the regression models under various criteria and calibration methods to provide the more accurate and precise results for pollutant load estimations.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 1995년도 추계 학술대회논문집
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• pp.154-159
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• 1995

Numerical optimization technique with Navier-Stokes code has been used to reduce the drag of conventional ogival nose. Forebody optimizations are performed for supersonic laminar and turbulent flow conditions. To alleviate the computing time of aerodynamic drag calculation, axisymmetric boundary condition is implemented in the 3-dimensional Navier-Stokes code. The automated optimization procedure with gradient based method results in a drag reduction of $4\;\%$.

• 대한임베디드공학회논문지
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• 제15권1호
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• pp.1-8
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• 2020

A derivation method for a quantized gradient for machine learning on an embedded system is proposed, in this paper. The proposed differentiation method induces the quantized gradient vector to an objective function and provides that the validation of the directional derivation. Moreover, mathematical analysis shows that the sequence yielded by the learning equation based on the proposed quantization converges to the optimal point of the quantized objective function when the quantized parameter is sufficiently large. The simulation result shows that the optimization solver based on the proposed quantized method represents sufficient performance in comparison to the conventional method based on the floating-point system.

• 한국정보전자통신기술학회논문지
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• 제10권2호
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• pp.192-197
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• 2017

본 논문은 저전력 영상 특징 추출 하드웨어 설계를 위한 공통 부분식 제거 기법 기반 이미지 필터 하드웨어 최적화 기법을 제안한다. 저전력 및 고성능 물체인식 하드웨어는 공장 자동화를 위한 산업용 로봇에 필수 모듈로 채택되고 있다. 따라서 물체인식 하드웨어의 영상 특징 추출 알고리즘에 다양하게 적용되는 Gaussian gradient 필터 하드웨어의 저면적 설계가 필수적이다. Gaussian gradient 필터의 하드웨어 복잡도를 줄이기 위해 필터에 사용되는 계수의 Symmetric한 특징과 Transposed form FIR 필터 하드웨어 구조를 이용했다. 제안된 이미지 필터의 하드웨어 구조는 알고리즘에 적용된 계수의 변형 없이 구현되었기 때문에 윤곽선 검출 알고리즘에 적용했을 때 검출 데이터의 열화 없이 구현될 수 있다. 제안된 이미지 필터 하드웨어 구조는 기존 구조와 비교했을 때 곱셈기의 수를 50% 절감할 수 있음을 확인했다.