• Title/Summary/Keyword: 구성 알고리즘

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인공 진화에 의한 학습 및 최적화

  • 장병탁
    • ICROS
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    • v.1 no.3
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    • pp.52-61
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    • 1995
  • 본 고에서는 진화계산의 동작 원리와 이론적 기반에 대해 살펴봄으로써 그 원리를 이해하고 앞으로의 응용가능성에 대하여 고찰하고자 한다. 이를 위해 먼저 대부분의 진화 알고리즘에 공통되는 기본 구성 요소와 계산절차를 기술하고, 진화 알고리즘을 이용하여 특정문제를 풀고자 할 때 고려할 사항에 대하여 기술한다. 다음에는 간단한 응용 문제를 예로 들어 이 문제에 진화 알고리즘을 적용하고 그 동작과정을 추적함으로써 실제 적용에 있어서의 여러 가지 결정사항과 그 수행과정을 구체적으로 살펴본다. 또한 진화 알고리즘의 이론적 배경을 이해하기 위해 스키마와 빌딩 블록 그리고 스키마 정리에 대해서 알아본다. 마지막으로 진화계산방식과 다른 지능적 계산 기술들과의 융합 가능성의 예로서, 유전 프로그래밍에 의한 신경망 구조의 설계 및 학습에 대하여 살펴본다.

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GPU Accelating of SIFT detection (SIFT 추출의 GPU 가속)

  • Seo, Kyoung-Taek;Kwon, Oh-Young
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.238-241
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    • 2015
  • 특징점 추출 알고리즘은 물체인식, 로보틱스, 비디오트래킹 등 많은 컴퓨터 비전 분야에 사용된다. 그 중 SIFT 알고리즘은 많은 계산량이 필요한 알고리즘으로 구성되어 있으므로 높은 화소의 이미지를 처리하기 위해서는 많은 시간이 소요되므로 GPU를 통한 가속이 필요하다. 본 논문에서는 NVIDIA GPU 장비를 사용하는 CUDA를 이용하여 SIFT 알고리즘을 병렬적으로 처리하여 4배 이상의 수행시간 감소 및 특징점이 많고 고해상도인 영상에서 효율이 더 높은 것을 확인하였다.

A Workflow-based Affiliation Network Knowledge Discovery Algorithm (워크플로우 협력네트워크 지식 발견 알고리즘)

  • Kim, Kwang-Hoon
    • Journal of Internet Computing and Services
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    • v.13 no.2
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    • pp.109-118
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    • 2012
  • This paper theoretically derives an algorithm to discover a new type of workflow-based knowledge from workflow models, which is termed workflow-based affiliation network knowledge. In general, workflow intelligence (or business process intelligence) technology consists of four types of techniques that discover, analyze, monitor and control, and predict a series of workflow-based knowledge from workflow models and their execution histories. So, this paper proposes a knowledge discovery algorithm which is able to discover workflow-based affiliation networks that represent the association and participation relationships between activities and performers defined in ICN-based workflow models. In order particularly to prove the correctness and feasibility of the proposed algorithm, this paper tries to apply the algorithm to a specific workflow model and to show that it is able to derive its corresponding workflow-based affiliation network knowledge.

Development of Simulation App for Understanding Test-and-Set Algorithms that Multi Learner Can Use Simultaneously

  • Lee, Kyong-ho
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.9
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    • pp.193-201
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    • 2020
  • In this study, we developed a simulation app that performs the Test-and-Set algorithm. The test-and-set algorithm is a highly difficult algorithm, so this simulation app was created for learners who have difficulty understanding it. Learners who want to understand the Test-and-Set algorithm gather to form a team, and use this simulation app to discuss and practice, and these teams can practice at the same time. The test-and-set, which is assumed to be a machine language, is not interrupted by using a queue, and it can be seen that the configured simulation app performs well in all three conditions of 'mutual exclusion', 'progress', and 'bounded waiting' that must be solved in the critical area problem.

An On-line Scheduling Algorithm for a GRID System (GRID시스템을 위한 온라인 스케줄링 알고리즘)

  • 김학두;김진석;박형우
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.1_2
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    • pp.95-101
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    • 2004
  • The scheduling problem that maps independent tasks to heterogeneous resources in distributed computing systems is known as NP-complete[1]. GRID[2] is an example of distributed systems that consisted of heterogeneous resources. Many algorithms to solve this problem have been presented[1,3,4,5]. The scheduling algorithm can be classified into static scheduling algorithms and dynmic scheduling algorithms. A dynamic scheduling algorithm can be used when we can not predict the priority of tasks. Moreover, a dynamic scheduling algorithm can be divided into on-line mode algorithm and batch mode algorithm according to the scheduling time[1,6]. In this paper, we propose a new on-line mode scheduling algorithm. By extensive simulation, we can see that our scheduling algorithm outperforms previous scheduling algorithms.

Adapted GSS Load Sharing Algorithm for Heterogeneous Cluster (이기종 클러스터를 위한 수정된 GSS 부하 분할 알고리즘)

  • Goo, Bon-geun
    • The KIPS Transactions:PartA
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    • v.10A no.4
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    • pp.331-338
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    • 2003
  • Cluster is the cost-effective parallel processing environment, and consists of the off-the-shelf computers connected by the computer net works. The characteristics of cluster are the node heterogeneity, the variety of node load, and the variety of network load. Because these characteristics influence the performance of parallel program executions, the load sharing for cluster is important, and by using the proper load sharing strategy, we can reduce the execution time of parallel programs. In this paper, we propose modified GSS algorithm, αGSS. In the proposed load sharing algorithms α GSS, the size of tasks are decided using the BogoMIPS of node. From the result of out experiments, we conclude that the proposed αGSS algorithm is effective in the heterogeneous cluster.

A Study on Diagnostics of Complex Performance Deterioration of Aircraft Gas-Turbine Engine Using Genetic Algorithms (유전자 알고리즘을 이용한 항공기용 가스터빈 엔진에 대한 복합 결함 진단에 대한 연구)

  • Kim, Seung-Min;Yong, Min-Chul;Roh, Tae-Seong;Choi, Dong-Whan
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2006.11a
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    • pp.285-288
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    • 2006
  • Genetic Algorithms(GA) which searches optimum solution using natural selection and the law of heredity has been applied to teaming algorithms in order to estimate performance deterioration of the aircraft gas turbine engine. The compressor, gas generation turbine and power turbine are considered for estimation for performance deterioration of a complex component at design point was conducted. As a result of that, complex defect diagnostics has been conducted. As a result, the accuracy of diagnostics were verified with its relative error with in 10% at each component.

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A Study on Diagnostics of Single Performance Deterioration of Aircraft Gas-Turbine Engine Using Genetic Algorithms (유전자 알고리즘을 이용한 항공기용 가스터빈 엔진의 단일 결함 진단에 대한 연구)

  • Kim, Seung-Min;Yong, Min-Chul;Roh, Tae-Seong;Choi, Dong-Whan
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.35 no.3
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    • pp.238-247
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    • 2007
  • Genetic Algorithms(GA) which searches optimum solution using natural selection and the law of heredity has been applied to learning algorithms in order to estimate performance deterioration of the aircraft gas turbine engine. The compressor, gas generator turbine and power turbine are considered for engine performance deterioration and estimation for performance deterioration of a single component at design point was conducted. As a result of that, defect diagnostics has been conducted. The input criteria for the genetic algorithm to guarantee the high stability and reliability was discussed as increasing learning data sets. As a result, the accuracy of defect estimation and diagnostics were verified with its RMS error within 3%.

Grouping of Wireless Terminals for High-Rate Transmission in Wireless LANs (무선랜에서 고속 데이터 전송을 위한 무선 단말들의 그룹화 알고리즘)

  • 우성제;이태진
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.3A
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    • pp.293-302
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    • 2004
  • Wireless LAN is a rather mature communication technology that connects mobile terminals. A typical wireless LAN system is composed of one AP and more than one terminals, which is called a BSS. Terminals near to an AP can receive high rate data but terminals far from an AP may not receive data with guaranteed high speed rate because received signal strength is weakened. This paper proposes a method to allow high speed data transmission by grouping terminals and using part of wireless terminals as repeaters. We compare and analyze proposed grouping algorithms based on Depth First Search and Breadth First Search via simulations. A grouping algorithm based on Breadth First Search is shown to be more effective in term of efficiency and coverage.

Modified GSS Algorithm for Heterogeneous Cluster (이기종 클러스터를 위한 수정된 GSS 알고리즘)

  • 구본근
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.405-408
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    • 2002
  • Cluster is the cost-effective parallel processing environment, and consists of the off-the-shelf computers connected by the computer networks. The characteristics of cluster are the node heterogeneity, the variety of node load, and the variety of network load. Because these characteristics influence the performance of parallel program executions, the load sharing for cluster is important, and by using the proper load sharing strategy, we can reduce the execution time of parallel programs. In this paper, we propose modified GSS algorithm, aGSS. In the proposed load sharing algorithms aGSS, the size of tasks are decided using the BogoMTPS of node. From the result of out experiments, we conclude that the proposed aGSS algorithm is effective in the heterogeneous cluster.

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