• 제목/요약/키워드: Fuzzy Reasoning Networks

검색결과 53건 처리시간 0.019초

효과적인 지식창출을 위한 웹 상의 지식채굴과정 : 주식시장에의 응용 (Knowledge Discovery Process from the Web for Effective Knowledge Creation: Application to the Stock Market)

  • 김경재;홍태호;한인구
    • 지식경영연구
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    • 제1권1호
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    • pp.81-90
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    • 2000
  • This study proposes the knowledge discovery process for the effective mining of knowledge on the web. The proposed knowledge discovery process uses the Prior knowledge base and the Prior knowledge management system to reflect tacit knowledge in addition to explicit knowledge. The prior knowledge management system constructs the prior knowledge base using a fuzzy cognitive map, and defines information to be extracted from the web. In addition, it transforms the extracted information into the form being handled in mining process. Experiments using case-based reasoning and neural network" are performed to verify the usefulness of the proposed model. The experimental results are encouraging and prove the usefulness of the proposed model.

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퍼지-뉴럴 제어기법에 의한 이동형 로봇의 자세 제어 (Orientation Control of Mobile Robot Using Fuzzy-Neural Control Technique)

  • 김종수
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1997년도 추계학술대회 논문집
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    • pp.82-87
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    • 1997
  • This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

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뉴럴-퍼지 제어기법에 의한 이동로봇의 지능제어기 설계 (Intelligent Control Design of Mobile robot Using Neural-Fuzzy Control Method)

  • 한성현
    • 한국공작기계학회논문집
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    • 제11권4호
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    • pp.62-67
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    • 2002
  • This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized loaming architecture. It is Proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tucking of the speed and azimuth of a mobile robot driven by two independent wheels.

뉴럴-퍼지제어기법에 의한 두 구동휠을 갖는 이동형 로보트의 자세 및 속도 제어 (The Azimuth and Velocity Control of a Mobile Robot with Two Drive Wheels by Neural-Fuzzy Control Method)

  • 조용길;배종일
    • 동력기계공학회지
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    • 제2권3호
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    • pp.74-82
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    • 1998
  • This paper presents a new approach to the design of speed and azimuth control of a mobile robot with two drive wheels. The proposed control scheme uses a Gaussian function as a unit function in the neural-fuzzy network and back propagation algorithm to train the neural-fuzzy network controller in the framework of the specialized learning architecture. It is proposed to a learned controller with two neural-fuzzy networks based on an independent reasoning and a connection net with fixed weights to simplify the neural-fuzzy network. The performance of the proposed controller can be seen by the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

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퍼지추론 및 뉴럴네트워크 기반 2휠구동 로봇의 주행제어알고리즘 개발 (Development of Travelling Control Algorithm Based Fuzzy Perception and Neural Network for Two Wheel Driving Robot)

  • 강언욱;양준석;차보남;박인수
    • 한국산업융합학회 논문집
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    • 제17권2호
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    • pp.69-76
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    • 2014
  • This paper proposes a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

퍼지신경망을 이용한 자율주행 이동로봇의 실시간 제어 (Real-Time Control for Autonomous Cruise of Mobile Robot Using Fuzzy Neural Network)

  • 정동연;이우송;한성현
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2003년도 춘계학술대회 논문집
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    • pp.1697-1700
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    • 2003
  • We propose a new technique for real-time controller design of a autonomous cruise mobile robot with three drive wheels. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and a back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The control performance of the proposed controller is illustrated by performing the computer simulation for trajectory tracking of the speed and azimuth of a autonomous cruise mobile robot driven by three independent wheels.

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이동로봇의 자율주행을 위한 실시간 퍼지신경망 제어 (Real-Time Fuzzy Neural Network Control for Real-Time Autonomous Cruise of Mobile Robot)

  • 정동연;김종수;한성현
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2003년도 춘계학술대회 논문집
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    • pp.312-318
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    • 2003
  • We propose a new technique for the cruise control system design of a mobile robot with three drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized teaming architecture. It is proposed a learning controller consisting of too neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by three independent wheels.

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뉴럴-퍼지제어기법에 의한 두 구동휠을 갖는 이동 로봇의 자세 및 속도 제어 (The Azimuth and Velocity Control of a Movile Robot with Two Drive Wheel by Neutral-Fuzzy Control Method)

  • 한성현
    • 한국해양공학회지
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    • 제11권1호
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    • pp.84-95
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    • 1997
  • This paper presents a new approach to the design speed and azimuth control of a mobile robot with drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the frmework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simple the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

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퍼지-신경망 제어기법을 이용한 Mobile Robot의 지능제어 (Intelligent Control of Mobile robot Using Fuzzy Neural Network Control Method)

  • 정동연;김용태;한성현
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2002년도 추계학술대회 논문집
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    • pp.235-240
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    • 2002
  • This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

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퍼지-신경회로망 제어기법에 의한 궤도차량의 지능제어 (An Intelligent Control of TRack Vehicle Using Fuzzy-Neural Network Control Method)

  • 신행봉;김용태;조길수;한성현
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1999년도 춘계학술대회 논문집
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    • pp.210-215
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    • 1999
  • In this paper, a new approach to the dynamic control technique for track vehicle system using fuzzy-neural network control technique is proposed. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle.

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