• 제목/요약/키워드: search algorithm

검색결과 3,898건 처리시간 0.028초

비 결정론적 최적화 기법을 이용한 선박의 CAE 모델링 자동화를 위한 지능형 에이전트 시스템의 개발 (Development of intelligent agent system for automated ship CAE modelling by non-deterministic optimized methods)

  • 배동명;김학수;신창혁;왕칭
    • 수산해양기술연구
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    • 제44권1호
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    • pp.57-67
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    • 2008
  • Recently, Korean shipbuilding industry is keeping up the position of world wide No. 1 in world shipbuilding market share. It is caused by endless efforts to develope new technologies and methods and fast development of IT technologies in Korea, to raise up its productivities and efficiency in shipbuilding industry with many kinds of optimizing methods including genetic algorithm or artificial life algorithm... etc. In this paper, we have suggested the artificial life algorithm with relay search micro genetic algorithm. and we have improved a defect of simple genetic algorithm for its slow convergence speed and added a variety of solution candidates with applying relay search simple genetic algorithm. Finally, we have developed intelligent agent system for ship CAE modeling. We have tried to offer some conveniences a ship engineer for repeated ship CAE modeling by changing ship design repeatedly and to increase its accuracy of a ship model with it.

휴리스틱 유전 알고리즘 경로 탐색에 광선 추적 알고리즘을 활용한 경로 최적화 연구 (Path Optimize Research used Ray-Tracing Algorithm in Heuristic-based Genetic Algorithm Pathfinding)

  • 고정운;이동엽
    • 한국게임학회 논문지
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    • 제19권6호
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    • pp.83-90
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    • 2019
  • 휴리스틱 기반의 유전 알고리즘 경로 탐색(H-GAP)은 노드, 에지 정보를 필요로 하지 않기 때문에 기존 경로 탐색 알고리즘의 단점을 보완하고 빠른 속도로 경로 탐색을 수행할 수 있다. 하지만 H-GAP를 이용해 탐색한 경로는 비 노드 기반이기 때문에 불필요한 경로 정보가 포함되어 탐색된 경로가 최적의 경로가 아닐 때도 있다. 본 논문에서는 H-GAP를 이용해 탐색한 경로를 최적화하는 알고리즘을 제안한다. 제안하는 알고리즘은 H-GAP의 경로 탐색이 완료된 후 광선 추적 알고리즘을 이용해 불필요한 경로 정보를 제거하여 경로를 최적화한다.

능동형 RFID시스템에서 태그 인식 속도 향상을 위한 고속 태그 충돌 방지 알고리즘 (High-Tag anti-collision algorithm to improve the efficiency of tag Identification in Active RFID System)

  • 이한영
    • 한국전자통신학회논문지
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    • 제7권2호
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    • pp.235-242
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    • 2012
  • 현재 RFID 시스템에서 해결하여야 할 가장 큰 문제 중 하나는 태그간의 충돌로 인해 인식 효율이 떨어진다는 것이다. 기존의 충돌 방식 중 BS 충돌 방지 알고리즘 방식은 구현이 간단하다는 장점이 있으나, 태그 수가 많아짐에 따라서 태그간 충돌에 의해 전체 태그를 읽는데 요구되는 단계별 스케줄 횟수가 증가하는 단점을 가지고 있다. 본 논문에서는 이 문제를 해결하기 위해서 충돌 예상을 최소화 하기 위해 사전에 '0'과 '1'의 결정 비트를 통해 복수의 응답 프레임(MF)을 제안한 방식을 제안하였다. 시뮬레이션 결과 복수 응답 프레임 (MF) 알고리즘은 기존의 알고리즘보다 30~50% 성능이 향상됨을 보인다는 것을 알 수 있었다.

개인화 알고리즘으로 필터 버블이 형성되는 과정에 대한 검증 (A Verification about the Formation Process of Filter Bubble with Personalization Algorithm)

  • 전준영;황소윤;윤영미
    • 한국멀티미디어학회논문지
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    • 제21권3호
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    • pp.369-381
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    • 2018
  • Nowadays a personalization algorithm is gaining huge attention. It gives users selective information which is helpful and interesting in a deluge of information based on their past behavior on the internet. However there is also a fatal side effect that the user can only get restricted information on restricted topics selected by the algorithm. Basically, the personalization algorithm makes users have a narrower perspective and even stronger bias because users have less chances to get views of opponent. Eli Pariser called this problem the 'filter bubble' in his book. It is important to understand exactly what a filter bubble is to solve the problem. Therefore, this paper shows how much Google's personalized search algorithm influences search result through an experiment with deep neural networks acting like users. At the beginning of the experiment, two Google accounts are newly created, not to be influenced by the Google's personalized search algorithm. Then the two pure accounts get politically biased by two methods. We periodically calculate the numerical score depending on the character of links and it shows how biased the account is. In conclusion, this paper shows the formation process of filter bubble by a personalization algorithm through the experiment.

병렬 적응 진화알고리즘을 이용한 발전기 기동정지계획에 관한 연구 (A Parallel Adaptive Evolutionary Algorithm for Thermal Unit Commitment)

  • 김형수;조덕환;문경준;이화석;박준호;황기현
    • 대한전기학회논문지:전력기술부문A
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    • 제55권9호
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    • pp.365-375
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    • 2006
  • This paper is presented by the application of parallel adaptive evolutionary algorithm(PAEA) to search an optimal solution of a thermal unit commitment problem. The adaptive evolutionary algorithm(AEA) takes the merits of both a genetic algorithm(GA) and an evolution strategy(ES) in an adaptive manner to use the global search capability of GA and the local search capability of ES. To reduce the execution time of AEA, the developed algorithm is implemented on an parallel computer which is composed of 16 processors. To handle the constraints efficiently and to apply to Parallel adaptive evolutionary algorithm(PAEA), the states of thermal unit are represented by means of real-valued strings that display continuous terms of on/off state of generating units and are involved in their minimum up and down time constraints. And the violation of other constraints are handled by repairing operator. The procedure is applied to the $10{\sim}100$ thermal unit systems, and the results show capabilities of the PAEA.

A Stigmergy-and-Neighborhood Based Ant Algorithm for Clustering Data

  • Lee, Hee-Sang;Shim, Gyu-Seok
    • Management Science and Financial Engineering
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    • 제15권1호
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    • pp.81-96
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    • 2009
  • Data mining, specially clustering is one of exciting research areas for ant based algorithms. Ant clustering algorithm, however, has many difficulties for resolving practical situations in clustering. We propose a new grid-based ant colony algorithm for clustering of data. The previous ant based clustering algorithms usually tried to find the clusters during picking up or dropping down process of the items of ants using some stigmergy information. In our ant clustering algorithm we try to make the ants reflect neighborhood information within the storage nests. We use two ant classes, search ants and labor ants. In the initial step of the proposed algorithm, the search ants try to guide the characteristics of the storage nests. Then the labor ants try to classify the items using the guide in-formation that has set by the search ants and the stigmergy information that has set by other labor ants. In this procedure the clustering decision of ants is quickly guided and keeping out of from the stagnated process. We experimented and compared our algorithm with other known algorithms for the known and statistically-made data. From these experiments we prove that the suggested ant mining algorithm found the clusters quickly and effectively comparing with a known ant clustering algorithm.

Training HMM Structure and Parameters with Genetic Algorithm and Harmony Search Algorithm

  • Ko, Kwang-Eun;Park, Seung-Min;Park, Jun-Heong;Sim, Kwee-Bo
    • Journal of Electrical Engineering and Technology
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    • 제7권1호
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    • pp.109-114
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    • 2012
  • In this paper, we utilize training strategy of hidden Markov model (HMM) to use in versatile issues such as classification of time-series sequential data such as electric transient disturbance problem in power system. For this, an automatic means of optimizing HMMs would be highly desirable, but it raises important issues: model interpretation and complexity control. With this in mind, we explore the possibility of using genetic algorithm (GA) and harmony search (HS) algorithm for optimizing the HMM. GA is flexible to allow incorporating other methods, such as Baum-Welch, within their cycle. Furthermore, operators that alter the structure of HMMs can be designed to simple structures. HS algorithm with parameter-setting free technique is proper for optimizing the parameters of HMM. HS algorithm is flexible so as to allow the elimination of requiring tedious parameter assigning efforts. In this paper, a sequential data analysis simulation is illustrated, and the optimized-HMMs are evaluated. The optimized HMM was capable of classifying a sequential data set for testing compared with the normal HMM.

특이값 분해를 이용한 치수측정 기반 디지털 트윈 알고리즘 경량화 (Lightweight Algorithm for Digital Twin based on Diameter Measurement using Singular-Value-Decomposition)

  • 이승민;박대진
    • 대한임베디드공학회논문지
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    • 제18권3호
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    • pp.117-124
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    • 2023
  • In the machine vision inspection equipment, diameter measurement is important process in inspection of cylindrical object. However, machine vision inspection equipment requires complex algorithm processing such as camera distortion correction and perspective distortion correction, and the increase in processing time and cost required for precise diameter measurement. In this paper, we proposed the algorithm for diameter measurement of cylindrical object using the laser displacement sensor. In order to fit circle for given four input outer points, grid search algorithms using root-mean-square error and mean-absolute error are applied and compared. To solve the limitations of the grid search algorithm, we finally apply the singular-value-decomposition based circle fitting algorithm. In order to compare the performance of the algorithms, we generated the pseudo data of the outer points of the cylindrical object and applied each algorithm. As a result of the experiment, the grid search using root-mean-square error confirmed stable measurement results, but it was confirmed that real-time processing was difficult as the execution time was 10.8059 second. The execution time of mean-absolute error algorithm was greatly improved as 0.3639 second, but there was no weight according to the distance, so the result of algorithm is abnormal. On the other hand, the singular-value-decomposition method was not affected by the grid and could not only obtain precise detection results, but also confirmed a very good execution time of 0.6 millisecond.

효과적인 조기 중단 기법을 위한 변형된 3단계 탐색 움직임 추정 알고리즘 (Modified 3-step Search Motion Estimation Algorithm for Effective Early Termination)

  • 양현철;이성수
    • 대한전자공학회논문지SD
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    • 제47권7호
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    • pp.70-77
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    • 2010
  • 움직임 추정은 동영상 압축에서 가장 많은 연산량을 차지하는 부분으로 막대한 연산량을 줄이기 위한 많은 고속 탐색 기법이 제안되어 왔다. 움직임 추정에서 가장 많은 연산량을 차지하는 SAD (sum-of-absolute difference) 계산의 경우, 연산량을 줄이기 위해 SAD 계산 중간에 지금까지 계산된 중간값이 지금까지 찾아진 최소 SAD를 넘을 경우 더 이상의 SAD 계산을 중단하고 다음 탐색으로 넘어가는 조기 중단 기법이 많이 사용되고 있다. 본 논문에서는 대표적인 고속 탐색 기법인 3단계 탐색기법을 변형하여 조기 중단이 자주 일어나도록 탐색 위치의 탐색 순서만을 적응적으로 재배열하는 움직임 추정 기법을 제안하였다. 모의 실험 결과, 제안하는 움직임 추정 기법은 추가 연산량이 거의 없이 기존의 3단계 탐색 기법에 비해 동일한 성능을 유지하면서 연산량을 17~30% 감소시켰다.

A Novel Hybrid Intelligence Algorithm for Solving Combinatorial Optimization Problems

  • Deng, Wu;Chen, Han;Li, He
    • Journal of Computing Science and Engineering
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    • 제8권4호
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    • pp.199-206
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    • 2014
  • The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integrates multi-population strategy, collaborative strategy, genetic strategy, and ant colony strategy, to avoid the premature phenomenon, dynamically balance the global search ability and local search ability, and accelerate the convergence speed. We select the traveling salesman problem to demonstrate the validity and feasibility of the NHGAO algorithm for solving complex optimization problems. The simulation experiment results show that the proposed NHGAO algorithm can obtain the global optimal solution, achieve self-adaptive control parameters, and avoid the phenomena of stagnation and prematurity.