• 한국농공학회지
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• 제44권2호
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• pp.127-135
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• 2002

Due to the fact that the design of a reinforced concrete structure changes in accordance with its shape and assigned load, total automation of the design system has not been achieved. For instance, since there is no general rule about setting up reinforcing steel quantity and arrangement location, it is simply not feasible to automatically decide the reinforcing arrangement location. In this study, the ESO(evolutionary structural optimization) technique and its related issues will be discussed. The ESO techniques is determined the reasonable load path which is traveling of load between in-flow and out-flow at a concrete structure using numerical analysis. And the results applied to the steel arrangement in reinforced concrete structures. The optimal algorithm, which determines the terminal criteria during ESO process, has been updated by using the obtained results. And the load path within the member has been determined automatically.

• 전기학회논문지
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• 제66권12호
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• pp.1799-1803
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• 2017

This paper introduces the prediction methods of windstorm advisory using GP nonlinear compensation and SVM. The existing special report prediction is not specialized for strong wind, such as windstorm, because it is based on the wide range of predicted values for wind speed from low to high. In order to improve the performance of strong wind reporting prediction, a method that can efficiently classify boundaries of strong wind is necessary. First, evolutionary nonlinear regression based compensation technique is applied to obtain more accurate values of prediction for wind speed using UM data. Based on the prediction wind speed, the windstorm advisory is determined. Second, SVM method is applied to classify directly using the data of UM predictors and windstorm advisory. Above two methods are compared to evaluate of the performances for the windstorm data in Jeju Island in South Korea. The data of 2007-2009, 2011 year is used for training, and 2012 year is used for test.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.43.2-43
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• 2001

In this paper, we consider the problems of the evolutionary designed neural networks structures by genetic algorithm. Neural networks has been applied to various application fields since back-propagation algorithm was proposed, e.g. function approximation, pattern or character recognition and so on. However, one of difficulties to use the neural networks. It is how to design the structure of the neural network. Researchers and users design networks structures and training parameters such as learning rate and momentum rate and so on, by trial and error based on their experiences. In the case of designing large scales neural networks, it is very hard work for manually design by try and error. For this difficulty, various structural learning algorithms have been proposed. Especially, the technique of using genetic algorithm for networks structures design has been ...

• 항공우주기술
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• 제7권1호
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• pp.61-67
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• 2008

무인항공기의 비행제어법칙 설계를 위하여 자동 제어기 이득 결정 프로그램을 개발하였다. 제어기 이득 결정 문제를 최적화 문제로 정식화 하고, 최적화 문제의 최적해로부터 제어기 이득을 결정하였다. 최적화 문제의 해를 계산하기 위해 진화연산기법의 하나인 PSO 알고리듬과 비선형 프로그래밍의 하나인 SQP 알고리듬을 연결하여 사용하였다. 이 방법을 통하여 최적해 계산 시간을 PSO 방법에 비하여 1/5로 감소시켰으며, 보다 정확한 최적해를 계산할 수 있었다.

• 전자공학회논문지
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• 제51권5호
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• pp.51-57
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• 2014

본 논문에서는 M-ary 홀로그래픽 데이터 저장장치에 적용 가능한 진화 연산 알고리즘 기반 적응적 문턱치 검출 기법을 제안한다. 전통적으로 유전 알고리즘은 생명체의 유전자 진화과정에 근간하여 최적 혹은 준최적 문제와 데이터 추정을 위해 사용되는 매우 유용한 기법이다. 본 연구에서는 픽셀 어긋남이 심화되는 2차원 홀로그래픽 채널 환경에서 데이터의 검출 성능을 향상시키기 위해서, 각 데이터 검출 영역의 문턱 값(threshold value)을 유전 알고리즘의 인구 집합(population set)의 해로 간주하여 비트 검출 영역을 적응적으로 선택하는 방법을 제안한다. 제안하는 기법의 성능을 평가하기 위해 픽셀 어긋남 현상이 심화된 4-ary 멀티레벨 입력의 홀로그래픽 채널 환경을 고려하고 모의실험을 수행하여 진화 연산의 세대수에 따른 비트오율 성능을 측정한다. 성능평가를 통해 기존의 비트 검출 기법과 비교함으로써 제안 기법의 우수성을 확인하였다.

• Steel and Composite Structures
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• 제47권2호
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• pp.147-165
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• 2023

The paper contrasts conventional seismic design with a design that incorporates buckling-restrained bracing in three-dimensional reinforced concrete buildings (BRBs). The suboptimal structures may be found using the multi-objective chimp optimization algorithm (MEN-ChOA). Given the constraints and dimensions, ChOA suffers from a slow convergence rate and tends to become stuck in local minima. Therefore, the ChOA is improved by niching and evolutionary operators to overcome the aforementioned problems. In addition, a new technique is presented to compute seismic and dead loads that include all of a structure's parts in an algorithm for three-dimensional frame design rather than only using structural elements. The performance of the constructed multi-objective model is evaluated using 12 standard multi-objective benchmarks proposed in IEEE congress on evolutionary computation. Second, MEN-ChOA is employed in constructing several reinforced concrete structures by the Mexico City building code. The variety of Pareto optimum fronts of these criteria enables a thorough performance examination of the MEN-ChOA. The results also reveal that BRB frames with comparable structural performance to conventional moment-resistant reinforced concrete framed buildings are more cost-effective when reinforced concrete building height rises. Structural performance and building cost may improve by using a nature-inspired strategy based on MEN-ChOA in structural design work.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.859-863
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• 2004

Structural Dynamics Modification is very effective technique to improve structure's dynamic characteristics by adding or removing auxiliary structures, changing material property, changing shape of structure. In this research, using the surface grooving technique, shape of base structure was changed to improve its first natural frequency. Utilizing the result of sensitivity analysis, groove shape was formed gathering the many small embossing elements. For this process, Sensitivity Criterion Factor was introduced. To reduce its amount of calculation, the range of target area was restricted to their neighboring area and that result was very successful.

• Advances in Computational Design
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• 제4권3호
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• pp.197-210
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• 2019

Motion generation of a four-bar linkage is a type of mechanism synthesis that has a wide range of applications such as a pick-and-place operation in manufacturing. In this research, the use of meta-heuristics for motion generation of a four-bar linkage is demonstrated. Three problems of motion generation were posed as a constrained optimization probably using the weighted sum technique to handle two types of tracking errors. A simple penalty function technique was used to deal with design constraints while three meta-heuristics including differential evolution (DE), self-adaptive differential evolution (JADE) and teaching learning based optimization (TLBO) were employed to solve the problems. Comparative results and the effect of the constraint handling technique are illustrated and discussed.

• 한국구조물진단유지관리공학회 논문집
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• 제18권4호
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• pp.1-9
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• 2014

최근 양자컴퓨터의 개발과 더불어 양자역학의 특성을 응용한 양자기반 탐색기법의 개발과 공학 문제에의 적용은 매우 흥미로운 연구주제 중 하나로 부각되고 있다. 이 알고리즘은 기본적으로 0과 1이 중첩되어진 양자비트를 이용하여 정보가 저장되고, 양자게이트 연산을 통해 해에 접근하게 된다. 이 과정에서 알고리즘은 탐사와 개척 두 가지 탐색 특성간의 균형이 자연스럽게 유지되며, 진화정보가 계속 누적된다는 장점으로 기존의 탐색법과 차별되어 새로운 알고리즘으로 평가되었다. 본 연구에서는 이와 같은 양자기반 진화알고리즘을 평면 트러스의 구조최적화에 적용하여 최소중량설계 기법을 제안하였다. 최적화 수리모형에서 비용함수는 최소중량이며, 제약함수는 변위와 응력에 관한 함수로 구성하였다. 진화정보의 누적과 수렴 과정을 알아보기 위해서 10부재 평면 트러스와 17부재 평면트러스 예제를 수치예제로 채택하여 결과를 분석하였다. 수치예제의 구조최적설계 결과에서 볼 때, 기존의 고전적 탐색기법의 연구결과와 비교해서 더 나은 최소중량 설계의 결과를 얻을 수 있었으며, 진화정보의 누적된 결과로 해의 정밀도를 관찰할 수 있었다. 또한 누적된 진화정보인 양자비트의 확률적 표현은 종료시점을 쉽게 판단할 수 있다.

• 한국전산유체공학회지
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• 제13권4호
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• pp.96-106
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• 2008

We review a series of studies on turbulent skin friction drag reduction in wall-turbulence recently conducted in Japan. First, an identity equation relating the skin friction drag and the Reynolds shearstress (the FIK identity) is introduced. Based on the implication of the FIK identity, a new analytical suboptimal feedback control law requiring the streamwise wall-shear stress only is introduced and direct numerical simulation (DNS) results of turbulent pipe flow with that control is reported. We also introduce DNS of an anisotropic compliant surface and parameter optimization using an evolutionary optimization technique.