• 대한전자공학회논문지
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• 제19권5호
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• pp.12-19
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• 1982

현재까지의 적응 필터(adaptive filter)의 설계 방법을 대별하면 국부 파라미타 최적화(local parameter optimization)방법[1]과 안정성(stability)을 주한점으로 하는 방법[1-3] 의 두 가지로 된다. 그리고 이들 중에서 비교적 간단한 방법은 로칼 파라미터 최적화 방법으로서, 이것에서는 스티피스트-디샌트(steepest-descent)방법[15]을 이용하는 LMS 알고리즘을 대표적인 것으로 들 수 있다. 적응 필터의 설계에 있어서 가장 중요한 것은 수검 속도를 높이는 일이다. 본 논문은 적응 비순환 필터의 설계를 위한 고속 수검 알고리즘을 개발하는 문제에 관하여 연구한 것으로, 적응 이득(adaptation-gain)을 적절히 조정함으로써, 종래 사용되어 오던 LMS 알고리즘 및 그의 변형인 여러 알고리즘에 비하여 수검 속도를 높일 수 있으며 동시에 안정성이 높은 새로운 알고리즘을 제시하였다. 그리고 제안된 알고리즘을 이용한 적응 필터의 특성 배선 문제를 다각도로 검토하였다.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1994년도 가을 학술발표회 논문집
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• pp.267-272
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• 1994

This work presents a method of optimum design for reinforced concrete building frames with rectangular cross sections. The optimization techniques used is based on the principle of divided parameters. The design variable parameters are divided into two groups, external and internal, and the optimization is also divided into external and internal procedure. This principle overcomes difficulties arising from the presence of two materials in one element, the property peculiar to reinforced concrete. Several search algorithms are tested to verify their accuracy for the external optimization. Among them pattern search algorithms has been found consistent. This work proposes a new method, modified pattern search, and a number of sample problems prove its accuracy and usefulness. Exhaustive search for all local minima in the design spaces for two sample problems has been carried out to understand the nature of the problem. The number of local minima identified is quite more than expected and it has become understood that the researcher's task in this field is to find a better local minimum if not global. The designs produced by the method preposed have been found better than those from other method, and they are in full accord with ACI Building Code Requirments(ACI 318-89).

• 대한전기학회논문지:시스템및제어부문D
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• 제50권11호
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• pp.532-540
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• 2001

In this paper, we propose a probabilistic tabu search strategy for function optimization. It is composed of two procedures, one is Basic search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify search region. In basic search procedure, we use Belief space and Near region to create neighbors. Belief space is made of high-rank neighbors to effectively restrict searching space, so it can improve searching time and local or global searching capability. When a solution is converged in a local area, Restarting procedure works to search other regions. In this time, we use Probabilistic Tabu Strategy(PTS) to adjust parameters such as a reducing rate, initial searching region etc., which makes enhance the performance of searching ability in various problems. In order to show the usefulness of the proposed method, the PTS is applied to the minimization problems such as De Jong functions, Ackley function, and Griewank functions etc., the results are compared with those of GA or EP.

• Nuclear Engineering and Technology
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• 제55권5호
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• pp.1527-1532
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• 2023

The noise reduction algorithm using the non-local means (NLM) approach is very efficient in nuclear medicine imaging. In this study, the applicability of the NLM noise reduction algorithm in single-photon emission computed tomography (SPECT) images with a brain phantom and the optimization of the NLM algorithm by changing the smoothing factors according to various reconstruction methods are investigated. Brain phantom images were reconstructed using filtered back projection (FBP) and ordered subset expectation maximization (OSEM). The smoothing factor of the NLM noise reduction algorithm determined the optimal coefficient of variation (COV) and contrast-to-noise ratio (CNR) results at a value of 0.020 in the FBP and OSEM reconstruction methods. We confirmed that the FBP- and OSEM-based SPECT images using the algorithm applied with the optimal smoothing factor improved the COV and CNR by 66.94% and 8.00% on average, respectively, compared to those of the original image. In conclusion, an optimized smoothing factor was derived from the NLM approach-based algorithm in brain SPECT images and may be applicable to various nuclear medicine imaging techniques in the future.

• Structural Engineering and Mechanics
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• 제46권3호
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• pp.403-416
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• 2013

This paper describes new optimization strategy that offers significant improvements in performance over existing methods for geometry design of frame structures. In this study, an imperialist competitive algorithm (ICA) and ant colony optimization (ACO) are combined to reach to an efficient algorithm, called Imperialist Competitive Ant Colony Optimization (ICACO). The ICACO applies the ICA for global optimization and the ACO for local search. The results of optimal geometry for three benchmark examples of frame structures, demonstrate the effectiveness and robustness of the new method presented in this work. The results indicate that the new technique has a powerful search strategies due to the modifications made in search module of ICACO. Higher rate of convergence is the superiority of the presented algorithm in comparison with the conventional mathematical methods and non hybrid heuristic methods such as ICA and particle swarm optimization (PSO).

• Structural Engineering and Mechanics
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• 제54권3호
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• pp.453-474
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• 2015

A hybrid approach of Particle Swarm Optimization (PSO) and Swallow Swarm Optimization algorithm (SSO) namely Hybrid Particle Swallow Swarm Optimization algorithm (HPSSO), is presented as a new variant of PSO algorithm for the highly nonlinear dynamic truss shape and size optimization with multiple natural frequency constraints. Experimentally validation of HPSSO on four benchmark trusses results in high performance in comparison to PSO variants and to those of different optimization techniques. The simulation results clearly show a good balance between global and local exploration abilities and consequently results in good optimum solution.

• Structural Engineering and Mechanics
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• 제77권6호
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• pp.779-795
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• 2021

In the recent decades, various optimization algorithms have been considered for the optimization of structures. In this research, a new enhanced algorithm is used for the size and topology optimization of truss structures. This algorithm, which is obtained from the combination of Crow Search Algorithm (CSA) and the Cellular Automata (CA) method, is called CA-CSA method. In the first iteration of the CA-CSA method, some of the best designs of the crow's memory are first selected and then located in the cells of CA. Then, a random cell is selected from CA, and the best design is chosen from the selected cell and its neighborhood; it is considered as a "local superior design" (LSD). In the optimization process, the LSD design is used to modify the CSA method. Numerical examples show that the CA-CSA method is more effective than CSA in the size and topology optimization of the truss structures.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 추계학술발표대회
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• pp.579-580
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• 2009

Proxy Mobile IPv6에서는 같은 Local Mobility Anchor 내의 다른 Mobile Access Gateway에 있는 Mobile Node들의 패킷 전송에 있어서 발생하는 삼각 라우팅 문제는 여전히 존재한다. 이 문제점을 해결하기 위해 인터넷 드래프트 Liebsch와 Dutta에서 제안된 두 가지 Route Optimization 기법의 동작 과정을 알아보고, 상호 데이터 전송 상황에서 더 나은 성능을 제공하는 Correspondent Route Optimization 기법을 제안한다. 제안한 Route Optimization 기법은 Correspondent Flag를 추가하여 Mobile Access Gateway 간 Corresponding Binding을 완료하여, Route Optimization을 설정한다. 제안한 Correspondent Route Optimization 기법은 기존의 기법보다 상호 데이터 전송 상황에서 Route Optimization에 필요한 메시지 수가 적기 때문에 시그널링 비용이 감소하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 춘계학술발표대회
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• pp.1218-1221
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• 2009

최근 Internet Engineering Task Force에서 표준화가 된 Proxy Mobile IPv6는 기존의 이동성 보장 프로토콜인 Mobile IPv6가 가지는 많은 문제점을 보완했다. 하지만, Proxy Mobile IPv6에서 같은 Local Mobility Anchor 내에 있고, 다른 Mobile Access Gateway에 있는 Mobile Node 사이의 패킷 전송에 있어서 발생하는 삼각 라우팅 문제는 여전히 존재한다. 이 문제점을 해결하기 위해 최근 Liebsch의 드래프트와 A.Dutta의 드래프트에서 제안된 두 가지의 Route Optimization 기법의 동작 과정을 알아보고, 상호 데이터 전송 상황에서 더 나은 성능을 제공하는 새로운 Route Optimization 기법을 제안한다. 제안한 Route Optimization 기법은 Corresponding Information을 이용하여 Mobile Access Gateway 간 Corresponding Binding을 완료하여, Route Optimization을 설정한다. 제안한 Correspondent Information을 이용한 Route Optimization 기법은 기존의 기법보다 상호 데이터 전송 상황에서 Route Optimization에 필요한 메시지 수가 적기 때문에 시그널링 비용이 감소하였다.

• 한국지능시스템학회논문지
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• 제14권1호
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• pp.15-19
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• 2004

개미군락시스템 (Ant Colony System, ACS)은 조합 최적화 문제를 해결하기 위한 기법으로 생물학적 기반의 메타휴리스틱 접근법이다. 지나간 경로에 대하여 페로몬을 분비하고 통신 매개물로 사용하는 실제 개미들의 추적 행위를 기반으로 한다. 최적 경로를 찾기 위해서는 보다 다양한 에지들에 대한 탐색이 필요하다. 기존 개미군락시스템의 지역 갱신 규칙에서는 지나간 에지에 대하여 고정된 페로몬 갱신 값을 부여하고 있다. 그러나 본 논문에서는 방문한 도시간의 거리와 해당 에지의 방문 횟수를 이용하여 페로몬을 부여한다. 보다 많은 정보를 탐색에 활용함으로써 기존의 방법에 비해 지역 최적화에 빠지지 않고 더 나은 해를 찾을 수 있었다.