• 제목/요약/키워드: behavior algorithm

검색결과 1,488건 처리시간 0.026초

군집 로봇 기반 공간 탐색을 위한 행동 제어 알고리즘 (Behavior Control Algorithm for Space Search Based on Swarm Robots)

  • 탁명환;주영훈
    • 전기학회논문지
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    • 제60권11호
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    • pp.2152-2156
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    • 2011
  • In this paper, we propose the novel behavior control algorithm by using the efficient searching method based on the characteristic of the swarm robots in unknown space. The proposed method consists of identifying the position and moving state of a robot by the dynamic modelling of a wheel drive vehicle, and planing behavior control rules of the swarm robots based on the sensor range zone. The cooperative search for unknown space is carried out by the proposed behavior control. Finally, some experiments show the effectiveness and the feasibility of the proposed method.

비정상행위 탐지 알고리즘 구현 및 성능 최적화 방안 (Implementation of abnormal behavior detection Algorithm and Optimizing the performance of Algorithm)

  • 신대철;김홍윤
    • 한국산학기술학회논문지
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    • 제11권11호
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    • pp.4553-4562
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    • 2010
  • 네트워크의 발달과 더불어 보안에 대한 중요성이 부각되면서 많은 침입탐지시스템이 개발되고 있다. 침입에 대한 다양한 침투기법을 미리 파악하여 패턴화시킴으로써 침입을 탐지하는 오용행위탐지와 알려진 침입뿐만 아니라 알려지지 않은 침입이나 비정상행위 탐지를 위한 비정상행위탐지 등이 그것이다. 현재 비정상행위탐지를 위한 통계적 방법 및 비정상적인 행위의 추출과 예측 가능한 패턴 생성을 위한 다양한 알고리즘 등이 연구되고 있다. 본 연구에서는 데이터 마이닝의 클러스터링 및 연관규칙을 사용하여 두 모델에 따른 탐지영역을 분석하여 대규모 네트워크에서의 침입탐지 시스템을 설계하는데 도움을 주고자 한다.

Optimum design of steel frame structures by a modified dolphin echolocation algorithm

  • Gholizadeh, Saeed;Poorhoseini, Hamed
    • Structural Engineering and Mechanics
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    • 제55권3호
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    • pp.535-554
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    • 2015
  • Dolphin echolocation (DE) optimization algorithm is a recently developed meta-heuristic in which echolocation behavior of Dolphins is utilized for seeking a design space. The computational performance of meta-heuristic algorithms is highly dependent to its internal parameters. But the computational time of adjusting these parameters is usually extensive. The DE is an efficient optimization algorithm as it includes few internal parameters compared with other meta-heuristics. In the present paper a modified Dolphin echolocation (MDE) algorithm is proposed for optimization of steel frame structures. In the MDE the step locations are determined using one-dimensional chaotic maps and this improves the convergence behavior of the algorithm. The effectiveness of the proposed MDE algorithm is illustrated in three benchmark steel frame optimization test examples. Results demonstrate the efficiency of the proposed MDE algorithm in finding better solutions compared to standard DE and other existing algorithms.

A New Convergence Behavior of the Least Mean K-power Adaptive Algorithm

  • Lee, Kang-Seung
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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    • pp.915-918
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    • 2001
  • In this paper we study a new convergence behavior of the least mean fourth (LMF) algorithm where the error raised to the power of four is minimized for a multiple sinusoidal input and Gaussian measurement noise. Here we newly obtain the convergence equation for the sum of the mean of the squared weight errors, which indicates that the transient behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant. It should be noted that no similar results can be expected from the previous analysis by Walach and Widrow.

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A New Convergence Behavior of the Least Mean Fourth Adaptive Algorithm for a Multiple Sinusoidal Input

  • Lee, Kang-Seung
    • 한국통신학회논문지
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    • 제26권12A호
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    • pp.2043-2049
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    • 2001
  • In this paper we study the convergence behavior of the least mean fourth(LMF) algorithm where the error raised to the power of four is minimized for a multiple sinusoidal input and Gaussian measurement noise. Here we newly obtain the convergence equation for the sum of the mean of the squared weight errors, which indicates that the transient behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant. It should be noted that no similar results can be expected from the previous analysis by Walach add Widrow.

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자율 이동 로봇의 정렬 군지능 알고리즘 구현 (Implementation of the Arrangement Algorithm for Autonomous Mobile Robots)

  • 김장현;공성곤
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 G
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    • pp.2186-2188
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    • 1998
  • In this paper, Fundamental rules governing group intelligence "arrangement" behavior of multiple number of autonomous mobile robots are represented by a small number of fuzzy rules. Complex lifelike behavior is considered as local interactions between simple individuals under small number of fundamental rules. The fuzzy rules for arrangement are generated from clustering the input-output data obtained from the arrangement algorithm. Simulation shows the fuzzy rules successfully realizes fundamental rules of the flocking group behavior.

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A New Result on the Convergence Behavior of the Least Mean Fourth Algorithm for a Multiple Sinusoidal Input

  • Lee, Kang-Seung
    • The Journal of the Acoustical Society of Korea
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    • 제18권2E호
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    • pp.3-9
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    • 1999
  • In this paper we study the convergence behavior of the least mean fourth(LMF) algorithm where the error raised to the power of four is minimized for a multiple sinusoidal input and Gaussian measurement noise. Here we newly obtain the convergence equation for the sum of the mean of the squared weight errors, which indicates that the transient behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant. It should be noted that no similar results can be expected from the previous analysis by Walach and Widrow/sup [1]/.

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클러스터링에 의한 자율 이동 로봇의 장애물 회피 알고리즘 (Implementation of the Obstacle Avoidance Algorithm of Autonomous Mobile Robots by Clustering)

  • 김장현;공성곤
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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    • pp.504-510
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    • 1998
  • In this paper, Fundamental rules governing group intelligence "obstacle avoidance" behavior of multiple autonomous mobile robots are represented by a small number of fuzzy rules. Complex lifelike behavior is considered as local interactions between simple individuals under small number of fundamental rules. The fuzzy rules for obstacle avoidance are generated from clustering the input-output data obtained from the obstacle avoidance algorithm. Simulation shows the fuzzy rules successfully realizes fundamental rules of the obstacle avoidance behavior.

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동적인 환경에서 강인한 멀티로봇 제어 알고리즘 연구 (Study for Control Algorithm of Robust Multi-Robot in Dynamic Environment)

  • 홍성우;안두성
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2001년도 춘계학술대회 논문집
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    • pp.249-254
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    • 2001
  • Abstract In this paper, we propose a method of cooperative control based on artifical intelligent system in distributed autonomous robotic system. In general, multi-agent behavior algorithm is simple and effective for small number of robots. And multi-robot behavior control is a simple reactive navigation strategy by combining repulsion from obstacles with attraction to a goal. However when the number of robot goes on increasing, this becomes difficult to be realized because multi-robot behavior algorithm provide on multiple constraints and goals in mobile robot navigation problems. As the solution of above problem, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for obstacle avoidance. Here, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for their direction to avoid obstacle. Our focus is on system of cooperative autonomous robots in environment with obstacle. For simulation, we divide experiment into two method. One method is motor schema-based formation control in previous and the other method is proposed by this paper. Simulation results are given in an obstacle environment and in an dynamic environment.

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대규모 무리 짓기에서 이웃 에이전트 탐색의 개선된 알고리즘 (An Improved Algorithm of Searching Neighbor Agents in a Large Flocking Behavior)

  • 이재문;정인환
    • 한국멀티미디어학회논문지
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    • 제13권5호
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    • pp.763-770
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    • 2010
  • 본 논문은 무리 짓기에서 공간분할 방법의 성능을 개선하는 알고리즘을 제안한다. 무리 짓기에서 여러 특성중의 하나는 두 에이전트가 공간적으로 가깝게 있다면 많은 공동 이웃들을 공유한다는 것이다. 본 논문은 이 특성을 적용하여 공간분할 방법을 개선한다. 기존의 공간분할 방법이 한 번에 하나의 에이전트에 대한 k개의 가장 가까운 이웃 에이전트들을 찾는 것에 반하여, 제안하는 방법은 에이전트들이 공간적으로 가까이 있다면 그들에 대하여 동시에 k개의 가장 가까운 이웃 에이전트들을 계산한다. 제안된 알고리즘은 구현되었으며, 그것의 성능은 기존의 공간분할 방법과 실험적으로 비교되었다. 비교의 결과로부터 제안하는 알고리즘이 기존의 방법을 평균적으로 33%정도 개선한다는 것을 알 수 있었다.