• 제목/요약/키워드: Intelligent Systems

검색결과 11,304건 처리시간 0.043초

학습자 행위 선호도에 기반한 적응적 학습 시스템 (An Adaptive Learning System based on Learner's Behavior Preferences)

  • 김용세;차현진;박선희;조윤정;윤태복;정영모;이지형
    • 한국HCI학회:학술대회논문집
    • /
    • 한국HCI학회 2006년도 학술대회 1부
    • /
    • pp.519-525
    • /
    • 2006
  • Advances in information and telecommunication technology increasingly reveal the potential of computer supported education. However, most computer supported learning systems until recently did not pay much attention to different characteristics of individual learners. Intelligent learning environments adaptive to learner's preferences and tasks are desired. Each learner has different preferences and needs, so it is very crucial to provide the different styles of learners with different learning environments that are more preferred and more efficient to them. This paper reports a study of the intelligent learning environment where the learner's preferences are diagnosed using learner models, and then user interfaces are customized in an adaptive manner to accommodate the preferences. In this research, the learning user interfaces were designed based on a learning-style model by Felder & Silverman, so that different learner preferences are revealed through user interactions with the system. Then, a learning style modeling is done from learner behavior patterns using Decision Tree and Neural Network approaches. In this way, an intelligent learning system adaptive to learning styles can be built. Further research efforts are being made to accommodate various other kinds of learner characteristics such as emotion and motivation as well as learning mastery in providing adaptive learning support.

  • PDF

Complex Process Control using the Adaptive Neural Fuzzy Inference System

  • Kim, Dong-Hwa
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
    • /
    • pp.351-351
    • /
    • 2000
  • Since the heat exchange system, such as the boiler of power plant, gas turbine, and radiator require an application of intelligent control system for a high rate heat efficiency and the efficiency of these systems is depended on the control methods it is important for operator to understand control system of these systems and intelligent control technologies. In order to properly apply control equipment and intelligent technology to these process control systems, it is necessary to understand fuzzy, neural network, genetics, and immune as well as the basic aspects and operation principle of the process that relate control, interrelationships of the process characteristics, and the dynamics that are involved. Generally, since PID controllers are used in these systems it is difficult far engineer to understand both the complex dynamics and the intelligent control method. In this paper, we design an effective experimental system for the intelligent control education and analyze its characteristics through experimental system and each intelligent method to study how they can learn intelligent control system by experiments.

  • PDF

Intelligent systems for control

  • Erickson, Jon D.
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
    • /
    • pp.4-12
    • /
    • 1996
  • This keynote presentation covers the subject of intelligent systems development for monitoring and control in various NASA space applications. Similar intelligent systems technology also has applications in terrestrial commercial applications. Discussion will be given of the general approach of intelligent systems and description given of intelligent systems under prototype development for possible use in Space Shuttle Upgrade, in the Experimental Crew Return. Vehicle, and in free-flying space robotic cameras to provide autonomy to these spacecraft with flexible human intervention, if desired or needed. Development of intelligent system monitoring and control for regenerative life support subsystems such as NASA's human rated Bio-PLEX test facility is also described. A video showing two recent world's firsts in real-time vision-guided robotic arm and hand grasping of tumbling and translating complex shaped objects in micro-gravity will also be shown.

  • PDF

Automatic Adaptive Space Segmentation for Reinforcement Learning

  • Komori, Yuki;Notsu, Akira;Honda, Katsuhiro;Ichihashi, Hidetomo
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제12권1호
    • /
    • pp.36-41
    • /
    • 2012
  • We tested a single pendulum simulation and observed the influence of several situation space segmentation types in reinforcement learning processes in order to propose a new adaptive automation for situation space segmentation. Its segmentation is performed by the Contraction Algorithm and the Cell Division Approach. Also, its automation is performed by "entropy," which is defined on action values’ distributions. Simulation results were shown to demonstrate the influence and adaptability of the proposed method.

Some Comments on and an Extension to Activity Structures for Intelligent Systems

  • Hall, Lawrence O.
    • 한국지능시스템학회논문지
    • /
    • 제3권1호
    • /
    • pp.23-28
    • /
    • 1993
  • Activity structures are a set of functional structures which may be used to provide a uniform framework for the description of information processing systems. The interaction of some aspects of activity structures is discussed. Intelligent systems, a subset of information handling systems, are the primary emphasis of this work. An extension to the functional structures of the activity structures is proposed. The proposed structure is a met a-structure which affects most elements of an intelligent system. The structure is concerned with describing the way uncertainty in an environment is handled by a system. An example is given which shows the importance of describing the uncertainty handling method(s) of an intelligent system.

  • PDF

Improvement of Three Mixture Fragrance Recognition using Fuzzy Similarity based Self-Organized Network Inspired by Immune Algorithm

  • Widyanto, M.R.;Kusumoputro, B.;Nobuhara, H.;Kawamoto, K.;Yoshida, S.;Hirota, K.
    • 한국지능시스템학회:학술대회논문집
    • /
    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
    • /
    • pp.419-422
    • /
    • 2003
  • To improve the recognition accuracy of a developed artificial odor discrimination system for three mixture fragrance recognition, Fuzzy Similarity based Self-Organized Network inspired by Immune Algorithm (F-SONIA) is proposed. Minimum, average, and maximum values of fragrance data acquisitions are used to form triangular fuzzy numbers. Then the fuzzy similarity treasure is used to define the relationship between fragrance inputs and connection strengths of hidden units. The fuzzy similarity is defined as the maximum value of the intersection region between triangular fuzzy set of input vectors and the connection strengths of hidden units. In experiments, performances of the proposed method is compared with the conventional Self-Organized Network inspired by Immune Algorithm (SONIA), and the Fuzzy Learning Vector Quantization (FLVQ). Experiments show that F-SONIA improves recognition accuracy of SONIA by 3-9%. Comparing to the previously developed artificial odor discrimination system that used FLVQ as pattern classifier, the recognition accuracy is increased by 14-25%.

  • PDF

Neural Network Compensation Technique for Standard PD-Like Fuzzy Controlled Nonlinear Systems

  • Song, Deok-Hee;Lee, Geun-Hyeong;Jung, Seul
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제8권1호
    • /
    • pp.68-74
    • /
    • 2008
  • In this paper, a novel neural fuzzy control method is proposed to control nonlinear systems. A standard PD-like fuzzy controller is designed and used as a main controller for the system. Then a neural network controller is added to the reference trajectories to form a neural-fuzzy control structure and used to compensate for nonlinear effects. Two neural-fuzzy control schemes based on two well-known neural network control schemes, the feedback error learning scheme and the reference compensation technique scheme as well as the standard PD-like fuzzy control are studied. Those schemes are tested to control the angle and the position of the inverted pendulum and their performances are compared.

철도분야 지능형교통체계 도입 전략 (Railway strategies for introducing intelligent transportation system)

  • 이준;문대섭;엄진기;김동희;진일경
    • 한국철도학회:학술대회논문집
    • /
    • 한국철도학회 2011년도 춘계학술대회 논문집
    • /
    • pp.1544-1549
    • /
    • 2011
  • Transportation Efficiency Act of 2009 System National Integrated Transportation System Efficiency Act and the revised Road Traffic in the center of the Intelligent Transportation Systems rail, sea and air transport sector is expanding in various areas to promote business and Industry is planning to. Accordingly, the introduction of Intelligent Transportation Systems Outlook and Direction of the railway sector and to provide a comprehensive introduction of Intelligent Transportation Systems rail sector has raised the need. In this paper, the introduction of Intelligent Transportation Systems rail sector strategy is presented as follows. First, the rail users a convenient rail-centric information system used. Second, the reliability and value-added operating system built for the creation of high-tech rail. Third, crime and accidents are implemented in a safe railway. The results of this paper, the railway sector through the national Intelligent Transportation Systems to develop and introduce strategies to provide operational direction is expected to be present.

  • PDF