• 제목/요약/키워드: Prediction Control

검색결과 2,203건 처리시간 0.041초

Generating Complicated Models for Time Series Using Genetic Programming

  • Yoshihara, Ikuo;Yasunaga, Moritoshi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.146.4-146
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    • 2001
  • Various methods have been proposed for the time series prediction. Most of the conventional methods only optimize parameters of mathematical models, but to construct an appropriate functional form of the model is more difficult in the first place. We employ the Genetic Programming (GP) to construct the functional form of prediction models. Our method is distinguished because the model parameters are optimized by using Back-Propagation (BP)-like method and the prediction model includes discontinuous functions, such as if and max, as node functions for describing complicated phenomena. The above-mentioned functions are non-differentiable, but the BP method requires derivative. To solve this problem, we develop ...

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A QoS Prediction Management System in Distributed Multimedia Networks

  • Ueno, Yoshito
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1996년도 Proceedings International Workshop on New Video Media Technology
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    • pp.95-100
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    • 1996
  • User's qualities of services (QoS) are the basic requirements involved in distributed multimedia systems. Considering ATM network, ATM adapter cannot control the end-to-end connection satisfying the user's QoS. This paper describes the new concept of a QoS prediction management system in the distributed network and the configuration of it's QoS prediction management architecture and also discusses it's algorithm.

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의사 결정 구조에 의한 오존 농도예측 (Forecasting Ozone Concentration with Decision Support System)

  • 김재용;김태헌;김성신;이종범;김신도;김용국
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.368-368
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    • 2000
  • In this paper, we present forecasting ozone concentration with decision support system. Since the mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, modeling of ozone prediction system has many problems and results of prediction are not good performance so far. Forecasting ozone concentration with decision support system is acquired to information from human knowledge and experiment data. Fuzzy clustering method uses the acquisition and dynamic polynomial neural network gives us a good performance for ozone prediction with ability of superior data approximation and self-organization.

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보조벡터 머신을 이용한 시계열 예측에 관한 연구 (A study on the Time Series Prediction Using the Support Vector Machine)

  • 강환일;정요원;송영기
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.315-315
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    • 2000
  • In this paper, we perform the time series prediction using the SVM(Support Vector Machine). We make use of two different loss functions and two different kernel functions; i) Quadratic and $\varepsilon$-insensitive loss function are used; ii) GRBF(Gaussian Radial Basis Function) and ERBF(Exponential Radial Basis Function) are used. Mackey-Glass time series are used for prediction. For both cases, we compare the results by the SVM to those by ANN(Artificial Neural Network) and show the better performance by SVM than that by ANN.

INS/GPS 결합 칼만필터의 측정치 스무딩 및 예측 (Smoothing and Prediction of Measurement in INS/GPS Integrated Kalman Filter)

  • 이태규;김광진;제창해
    • 제어로봇시스템학회논문지
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    • 제7권11호
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    • pp.944-952
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    • 2001
  • Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it is desired to combine INS with external aids such as GPS. However GPS informations have a randomly abrupt jump due to a sudden corruption of the received satellite signals and environment, and moreover GPS can\`t provide navigation solutions. In this paper, smoothing and prediction schemes are proposed for GPS`s jump or unavailable GPS. The smoothing algorithm which is designed as a scalar adaptive filter, smooths abrupt jump. The prediction algorithm which is proved by Schuler error model of INS, estimates INS error in appropriate time. The outputs of proposed algorithm apply stable measurements to GPS aided INS Kalman filter. Simulations show that the proposed algorithm can effectively remove measurement jump and predict INS error.

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전기자동차 베터리 차단장치의 이론적 수명 예측에 대한 연구 (The Theoretical Life Prediction of Battery Disconnecting System for Electric Vehicle)

  • 류행수;박홍태
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.864-865
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    • 2011
  • Battery Disconnecting System (BDS) is the important equipment in electric vehicle system. Therefore, most of electric vehicle companies, i.e. Hyundai Motors, Renault Motors, General Motors, want to have the reliability of 15 years - 150, 000 miles. Recently, reliability prediction through Siemens Norm SN 29500 is considered without testing. In this paper, we will introduce the standard and various input parameters. Also the case study will be shown for BDS. Prediction model is constructed by listing all the components of BDS. It calculates the $\pi$ factors for each components using the conversion equation in the standard and converts the reference failure rates to the expected operating failure rates. According to the result, the parts which will be improved are EV-Relays.

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항공기 지상 활주 연료소모량 예측모델 사례연구 (A380 중심) (A Case Study of Aircraft Taxi Fuel Consumption Prediction Model (A380 Case))

  • 장성우;이영재;유광의
    • 한국항공운항학회지
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    • 제28권2호
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    • pp.29-35
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    • 2020
  • In this paper, we established a prediction model of fuel consumption at the aircraft's taxi operation. To look for countermeasures to reduce fuel consumption and carbon emissions, Airbus A380's actual ground taxi data was used. As a result, the number of stops or turnings during the taxi operation was not related to fuel consumption. It was confirmed that the amount of fuel consumption in the taxi operation was the taxi time and the thrust change. It can be confirmed that ground control optimization, which is the result of close cooperation between the control organization and the airline, is absolutely necessary to reduce taxi time and minimize the occurrence of thrust change events.

Safety Critical 시스템의 센서 결함 허용을 위한 Kalman Hybrid Redundancy 개발 (Development of Kalman Hybrid Redundancy for Sensor Fault-Tolerant of Safety Critical System)

  • 김만호;이석;이경창
    • 제어로봇시스템학회논문지
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    • 제14권11호
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    • pp.1180-1188
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    • 2008
  • As many systems depend on electronics, concern for fault tolerance is growing rapidly in the safety critical system such as intelligent vehicle. In order to make system fault tolerant, there has been a body of research mainly from aerospace field including predictive hybrid redundancy by Lee. Although the predictive hybrid redundancy has the fault tolerant mechanism to satisfy the fault tolerant requirement of safety crucial system such as x-by-wire system, it suffers form the variability of prediction performance according to the input feature of system. As an alternative to the prediction method of predictive hybrid redundancy for robust fault tolerant, Kalman prediction has attracted some attention because of its well-known and often-used with its structure called Kalman hybrid redundancy. In addition, several numerical simulation results are given where the Kalman hybrid redundancy outperforms with predictive smoothing voter.

CFD를 사용한 평행 홈 펌프 시일의 해석 개선 (Improvement on Prediction of Circumferential-Groove-Pump Seal with CFD Analysis)

  • 하태웅
    • Tribology and Lubricants
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    • 제24권6호
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    • pp.291-296
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    • 2008
  • In order to improve the leakage prediction and rotordynamic analysis of an annular seal with a smooth rotor and circumferentially grooved stator, CFD analysis using FLUENT has been performed to determine the groove penetration angle a which is the angle of separation line between control volumes II and III in groove section of Ha and Lee's three-control-volume theory. Validation to the present analysis using new penetration angle determined by the CFD analysis is achieved by comparisons with the results of published Ha and Lee's analysis. For the leakage prediction the present analysis shows slight improvement and CFD results yields the best. Direct damping and cross-coupled stiffness coefficients are predicted better to the experimental ones. However, direct stiffness coefficient is predicted worse.

계층 최적화 기법에 의한 비선형 계통의 최적 제어에 관한 연구 (A study on the hierachical optimization methods for the optimal control of nonlinear systems)

  • 천희영;박귀태;이종렬;이희정
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(I)
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    • pp.129-134
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    • 1987
  • In this paper, "Revised two-level costate prediction method" is developed to optimize the quadratic performance of a class of nonlinear dynamic systems. To show the merit, of this algorithm, the proposed algorithm is compared With "The new prediction method" and "Two-level costate prediction method". Advantages of this algorithm are illustrated by applying it to three examples, turbine generator system, fermentation Process, power control system in nuclear reactor.

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