• Title/Summary/Keyword: Quadratic Model

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Prediction Analysis of the Quadratic Errors-in-Variables Model (이차 변수 오차 모형의 예측분석)

  • Byeon, Jae-Hyeon;Lee, Seung-Hun
    • Journal of Korean Society for Quality Management
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    • v.21 no.1
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    • pp.152-160
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    • 1993
  • In developing a quadratic regression relationship, independent variable is frequently measured with error. In this paper the integrated mean square error of prediction is developed for a quadratic functional relationship model as a measure of the effect of measurement error of the independent variable on the predicted values. The amount of the effect of error is presented and illustrated with an example.

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Exact $D_S-efficient$ Designs for Quadratic Response Surface Model

  • Lim, Yong B.
    • Journal of the Korean Statistical Society
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    • v.20 no.2
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    • pp.156-161
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    • 1991
  • Exact $D_{s}$-efficient designs for the precise estimation of all the coefficients of the quadratic terms are studied in a quadratic response surface model. Efficient exact designs are constructed for 2 q 5 w.r.t. $D_{s}$-optimaity criterion based on Pesotchinsky's(1975) and approximate $D_{s}$-optimal design given in Lim & Studden(1988) . Moreover, they seem to have reasonably good D-efficiencies. Similar idea could apply to q$\geq$6 cases.

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An Application of Inverse Linear Quadratic Control to Strip Rolling Mill (철강 압연공정에의 ILQ(Inverse Linear Quadratic) 제어의 응용)

  • 최승갑
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.38-38
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    • 2000
  • To fulfill recent requirements for high quality products in steel rolling process, fast responding and easily tunab control system is required and ILQ(Inverse Linear Quadratic) control system may be one of such alternatives. In this paper characteristics of ILQ control and its application to BUR(Back-Up-Roll) eccentricity in strip rolling mill is discussed and compared to polynomial control approaches. Also the rolling mill model and basic principle to control thickness of srip are introduced with control effect by polynomial methods.

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2-D SU/PG Finite Element Model Using Quadratic Elements (2차 요소를 이용한 2차원 상향가중 유한요소모형)

  • Choi, Seung-Yong;Kim, Byung-Hyun;Kim, Sang-Ho;Han, Kun-Yeun
    • Journal of Korea Water Resources Association
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    • v.42 no.12
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    • pp.1053-1067
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    • 2009
  • The objective of this study is to develop an efficient and accurate quadratic finite element model based on Streamline Upwind/Petrov Galerkin (SU/PG) scheme for analyzing and predicting two dimensional flow features in complex natural rivers. For a development of model, quadratic tin, quadrilateral and mixed elements as well as linear tin, quadrilateral and mixed elements were used in the model. Also, this model was developed through reinforcement of Gauss Quadrature which was necessary to integral of governing equation. Several tests for bottom-rising channel and U-type channel were performed for the purpose of validation and verification of the developed model. Such results showed that solutions of second order elements are better accurate and improved than those of linear elements. Results obtained by the developed model and RMA-2 model are compared, and the results for the developed model were better accurate than those of RMA-2 model. In the future if the developed model is applied in natural rivers, it can provide better accurate results than those of existing model.

Estimating Fuzzy Regression with Crisp Input-Output Using Quadratic Loss Support Vector Machine

  • Hwang, Chang-Ha;Hong, Dug-Hun;Lee, Sang-Bock
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.10a
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    • pp.53-59
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    • 2004
  • Support vector machine(SVM) approach to regression can be found in information science literature. SVM implements the regularization technique which has been introduced as a way of controlling the smoothness properties of regression function. In this paper, we propose a new estimation method based on quadratic loss SVM for a linear fuzzy regression model of Tanaka's, and furthermore propose a estimation method for nonlinear fuzzy regression. This approach is a very attractive approach to evaluate nonlinear fuzzy model with crisp input and output data.

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Design and its Application of Robust Degital Optimal Model Following Servo System (강인한 디지털 최적모델 추종형 서보시스템의 구성과 그 적용)

  • 이양우;김정택;황창선
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.43 no.7
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    • pp.1186-1192
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    • 1994
  • This paper presents an algorithm to design a robust digital model following servo control system in which optimal linear quadratic regulator problem is used to design the control system that make the step/ramp response of the plant kept close to a specified ideal step/ramp response of the model. The quadratic criterion function for a continuous system is used to design the robust digital servo control system. The feasibility of the design technique is shown by the simulation and the proposed method is applied to the speed control of DC servo motor.

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Quadratic Programming Approach to Pansharpening of Multispectral Images Using a Regression Model

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.24 no.3
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    • pp.257-266
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    • 2008
  • This study presents an approach to synthesize multispectral images at a higher resolution by exploiting a high-resolution image acquired in panchromatic modality. The synthesized images should be similar to the multispectral images that would have been observed by the corresponding sensor at the same high resolution. The proposed scheme is designed to reconstruct the multispectral images at the higher resolution with as less color distortion as possible. It uses a regression model of the second order to fit panchromatic data to multispectral observations. Based on the regression model, the multispectral images at the higher spatial resolution of the panchromatic image are optimized by a quadratic programming. In this study, the new method was applied to the IKONOS 1m panchromatic and 4m multispectral data, and the results were compared with them of several current approaches. Experimental results demonstrate that the proposed scheme can achieve significant improvement over other methods.

A Globally Stabilizing Model Predictive Controller for Neutrally Stable Linear Systems with Input Constraints

  • Yoon, Tae-Woong;Kim, Jung-Su;Jadbabaie, Ali;Persis, Claudio De
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1901-1904
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    • 2003
  • MPC or model predictive control is representative of control methods which are able to handle physical constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global aymptotic stability can be obtained; until recently, use of infinite horizons was thought to be inevitable in this case. A globally stabilizing finite-horizon MPC has lately been suggested for neutrally stable continuous-time systems using a non-quadratic terminal cost which consists of cubic as well as quadratic functions of the state. The idea originates from the so-called small gain control, where the global stability is proven using a non-quadratic Lyapunov function. The newly developed finite-horizon MPC employs the same form of Lyapunov function as the terminal cost, thereby leading to global asymptotic stability. A discrete-time version of this finite-horizon MPC is presented here. The proposed MPC algorithm is also coded using an SQP (Sequential Quadratic Programming) algorithm, and simulation results are given to show the effectiveness of the method.

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Efficient Approximation Method for Constructing Quadratic Response Surface Model

  • Park, Dong-Hoon;Hong, Kyung-Jin;Kim, Min-Soo
    • Journal of Mechanical Science and Technology
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    • v.15 no.7
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    • pp.876-888
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    • 2001
  • For a large scaled optimization based on response surface methods, an efficient quadratic approximation method is presented in the context of the trust region model management strategy. If the number of design variables is η, the proposed method requires only 2η+1 design points for one approximation, which are a center point and tow additional axial points within a systematically adjusted trust region. These design points are used to uniquely determine the main effect terms such as the linear and quadratic regression coefficients. A quasi-Newton formula then uses these linear and quadratic coefficients to progressively update the two-factor interaction effect terms as the sequential approximate optimization progresses. In order to show the numerical performance of the proposed method, a typical unconstrained optimization problem and two dynamic response optimization problems with multiple objective are solved. Finally, their optimization results compared with those of the central composite designs (CCD) or the over-determined D-optimality criterion show that the proposed method gives more efficient results than others.

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Fast Elliptic Object Reconstruction from Projections by Support Estimation (서포트 추정을 이용한 빠른 이미지 사영 기반 타원형 물체 복원 기법)

  • Ko, Kyeong-Jun;Lee, Jung-Woo
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.105-106
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    • 2007
  • We present a fast reconstruction technique for elliptic objects, which can be applied to real-time computer tomography (CT) for simple geometric objects. It will be also shown that only 3 projections are needed to reconstruct an ellipse. A piecewise quadratic model is also proposed for more efficient Kalman filter based support estimation, which is used for the fast reconstruction technique. The performance of the piecewise quadratic model is compared with that of the existing piecewise linear model. Simulation results for the fast reconstruction are also presented.

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