• 제목/요약/키워드: Robust Search Algorithm

검색결과 152건 처리시간 0.026초

유전 알고리즘 기반의 강인한 성능을 가지는 모델추종형 보일러-터빈 H∞ 제어 시스템의 설계 (A Design of GA-Based Model-Following Boiler-Turbine H∞ Control System Having Robust Performance)

  • 황현준
    • Journal of Advanced Marine Engineering and Technology
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    • 제36권1호
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    • pp.126-132
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    • 2012
  • 본 연구에서는 강인한 성능을 가지는 모델추종형 H${\infty}$ 제어기의 설계법을 제시한다. 이를 위해 강인한 성능을 보장하는 해집단내에서 기준모델의 출력을 최적으로 추종하도록 유전 알고리즘을 사용하여 가중치 함수와 설계 파라미터 ${\gamma}$를 동시에 최적화한다. 설계된 H${\infty}$ 제어기는 강인한 성능에 관한 필요충분조건식을 만족함은 물론 설계사양에 따른 만족스러운 응답특성을 가진다. 제시된 방법을 보일러-터빈 제어 시스템에 적용하여 그 유용성을 확인한다.

Robust Visual Tracking using Search Area Estimation and Multi-channel Local Edge Pattern

  • Kim, Eun-Joon
    • 한국컴퓨터정보학회논문지
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    • 제22권7호
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    • pp.47-54
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    • 2017
  • Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

효율적인 움직임 추정을 위한 고속 블록 정합 알고리듬의 적응적 선택 (Adaptive Selection of Fast Block Matching Algorithms for Efficient Motion Estimation)

  • 김정준;전광길;정제창
    • 한국통신학회논문지
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    • 제33권1C호
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    • pp.19-33
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    • 2008
  • 본 논문에서는 기존의 고속 움직임 추정 방법과 새롭게 제안하는 고속 움직임 추정 방법들을 적응적으로 사용하는 기법을 제공한다. 이 알고리듬의 이름은 AUDC이며, 새롭게 제안하는 고속 움직임 추정 방법은 다이아몬드 탐색와 3단계 탐색 기법을 기초로 한다. 비록 많은 고속 움직임 추정 방법들이 각각 많은 장점을 가지고 있지만 단점도 가지고 있다. 그러므로 한가지의 고속 움직임 추정 방법을 사용하는 것보다는 적응적으로 고속 움직임 추정 기법을 선택하여 사용하는 것이 더욱 효율적이라 할 수 있다. 그래서 제안하는 움직임 추정 기법은 현재 블록에 이웃하는 블록의 Motion Vector의 길이, 탐색점의 수, SAD를 이용하여 다이아몬드 탐색 기법, 십자 3단계 탐색 기법 그리고 개량된 십자 다이아몬드 기법을 적응적으로 사용한다. 실험결과 AUDC는 많이 알려진 다른 고속 움직임 추정 방법보다 화질을 향상시킬 뿐만 아니라 탐색점의 수 또한 향상됨을 알 수 있다.

배전계통 최적 재구성 문제에 PC 클러스터 시스템을 이용한 병렬 유전 알고리즘-타부 탐색법 구현 (Parallel Genetic Algorithm-Tabu Search Using PC Cluster System for Optimal Reconfiguration of Distribution Systems)

  • 문경준;송명기;김형수;김철홍;박준호;이화석
    • 대한전기학회논문지:전력기술부문A
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    • 제53권10호
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    • pp.556-564
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    • 2004
  • This paper presents an application of parallel Genetic Algorithm-Tabu Search(GA-TS) algorithm to search an optimal solution of a reconfiguration in distribution system. The aim of the reconfiguration of distribution systems is to determine switch position to be opened for loss minimization in the radial distribution systems, which is a discrete optimization problem. This problem has many constraints and very difficult to solve the optimal switch position because it has many local minima. This paper develops parallel GA-TS algorithm for reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10% of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node aster predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium Ⅳ CPU and is connected with others through ethernet switch based fast ethernet. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution systems in the reference paper. From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution qualify. speedup. efficiency and computation time.

Parallel Genetic Algorithm-Tabu Search Using PC Cluster System for Optimal Reconfiguration of Distribution Systems

  • Mun Kyeong-Jun;Lee Hwa-Seok;Park June-Ho
    • KIEE International Transactions on Power Engineering
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    • 제5A권2호
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    • pp.116-124
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    • 2005
  • This paper presents an application of the parallel Genetic Algorithm-Tabu Search (GA- TS) algorithm, and that is to search for an optimal solution of a reconfiguration in distribution systems. The aim of the reconfiguration of distribution systems is to determine the appropriate switch position to be opened for loss minimization in radial distribution systems, which is a discrete optimization problem. This problem has many constraints and it is very difficult to solve the optimal switch position because of its numerous local minima. This paper develops a parallel GA- TS algorithm for the reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10$\%$ of the population to enhance the local searching capabilities. With migration operation, the best string of each node is transferred to the neighboring node after predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based rapid Ethernet. To demonstrate the usefulness of the proposed method, the developed algorithm was tested and is compared to a distribution system in the reference paper From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution quality, speedup, efficiency, and computation time.

Research on Robust Stability Analysis and Worst Case Identification Methods for Parameters Uncertain Missiles

  • Hou, Zhenqian;Liang, Xiaogeng;Wang, Wenzheng
    • International Journal of Aeronautical and Space Sciences
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    • 제15권1호
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    • pp.63-73
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    • 2014
  • For robust stability analysis of parameters uncertainty missiles, the traditional frequency domain method can only analyze each respective channel at several interval points within uncertain parameter space. Discontinuous calculation and couplings between channels will lead to inaccurate analysis results. A method based on the ${\nu}$-gap metric is proposed, which is able to comprehensively evaluate the robust stability of missiles with uncertain parameters; and then a genetic-simulated annealing hybrid optimization algorithm, which has global and local searching ability, is used to search for a parameters combination that leads to the worst stability within the space of uncertain parameters. Finally, the proposed method is used to analyze the robust stability of a re-entry missile with uncertain parameters; the results verify the feasibility and accuracy of the method.

A Hybrid Metaheuristic for the Series-parallel Redundancy Allocation Problem in Electronic Systems of the Ship

  • Son, Joo-Young;Kim, Jae-Hwan
    • Journal of Advanced Marine Engineering and Technology
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    • 제35권3호
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    • pp.341-347
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    • 2011
  • The redundancy allocation problem (RAP) is a famous NP.complete problem that has beenstudied in the system reliability area of ships and airplanes. Recently meta-heuristic techniques have been applied in this topic, for example, genetic algorithms, simulated annealing and tabu search. In particular, tabu search (TS) has emerged as an efficient algorithmic approach for the series-parallel RAP. However, the quality of solutions found by TS depends on the initial solution. As a robust and efficient methodology for the series-parallel RAP, the hybrid metaheuristic (TSA) that is a interactive procedure between the TS and SA (simulated annealing) is developed in this paper. In the proposed algorithm, SA is used to find the diversified promising solutions so that TS can re-intensify search for the solutions obtained by the SA. We test the proposed TSA by the existing problems and compare it with the SA and TS algorithm. Computational results show that the TSA algorithm finds the global optimal solutions for all cases and outperforms the existing TS and SA in cases of 42 and 56 subsystems.

Analysis of trusses by total potential optimization method coupled with harmony search

  • Toklu, Yusuf Cengiz;Bekdas, Gebrail;Temur, Rasim
    • Structural Engineering and Mechanics
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    • 제45권2호
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    • pp.183-199
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    • 2013
  • Current methods of analysis of trusses depend on matrix formulations based on equilibrium equations which are in fact derived from energy principles, and compatibility conditions. Recently it has been shown that the minimum energy principle, by itself, in its pure and unmodified form, can well be exploited to analyze structures when coupled with an optimization algorithm, specifically with a meta-heuristic algorithm. The resulting technique that can be called Total Potential Optimization using Meta-heuristic Algorithms (TPO/MA) has already been applied to analyses of linear and nonlinear plane trusses successfully as coupled with simulated annealing and local search algorithms. In this study the technique is applied to both 2-dimensional and 3-dimensional trusses emphasizing robustness, reliability and accuracy. The trials have shown that the technique is robust in two senses: all runs result in answers, and all answers are acceptable as to the reliability and accuracy within the prescribed limits. It has also been shown that Harmony Search presents itself as an appropriate algorithm for the purpose.

유전자 알고리즘과 군집 분석을 이용한 확률적 시뮬레이션 최적화 기법 (Genetic Algorithm and Clustering Technique for Optimization of Stochastic Simulation)

  • 이동훈;허성필
    • 한국군사과학기술학회지
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    • 제2권1호
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    • pp.90-100
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    • 1999
  • 유전자 알고리즘은 전통적인 등반 알고리즘을 이용하여 구하기 어려웠던 최적화 문제를 해결하기 위한 강인한(Robust) 탐색 기법이다. 특히 목적함수가 (1)여러 개의 국부 최대치를 가지는 경우, (2)수학적으로 표현이 불가능하거나 어려운 경우, (3)목적함수에 교란 항(disturbance term)이 섞여 있을 경우도 우수한 탐색 능력을 갖는 것으로 알려져 있다. 본 논문에서는 유전자 알고리즘을 이용하여 나타나는 다양한 해집합을 형성하는 개체군을 군집성 분석(cluster analysis)을 이용하여 군집화하고, 각 군집에 부여된 군집 적합도에 따라서 최적해를 구함으로써 단순 유전자 알고리즘에 의한 최적화보다 훨씬 향상된 탐색 알고리즘을 제안하였다. 반응표면의 형태가 정형화한 테스트 함수의 형태로 나타난다고 가정한 경우에 대하여 몬테 칼로 시뮬레이션을 통하여 본 알고리즘을 적용하여 평가하고 분석하였다.

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강건한 특징점 추출을 이용한 철강제품 정보 검출을 위한 전처리 알고리즘 (Pre-processing Algorithm for Detection of Slab Information on Steel Process using Robust Feature Points extraction)

  • 최종현;윤종필;최성후;구근휘;김상우
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 제39회 하계학술대회
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    • pp.1819-1820
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    • 2008
  • Steel slabs are marked with slab management numbers (SMNs). To increase efficiency, automated identification of SMNs from digital images is desirable. Automatic extraction of SMNs is a prerequisite for automatic character segmentation and recognition. The images include complex background, and the position of the text region of the slabs is variable. This paper describes an pre-processing algorithm for detection of slab information using robust feature points extraction. Using SIFT(Scale Invariant Feature Transform) algorithm, we can reduce the search region for extraction of SMNs from the slab image.

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