• Title/Summary/Keyword: the least-squares method

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EFFICIENT ESTIMATION OF THE REGULARIZATION PARAMETERS VIA L-CURVE METHOD FOR TOTAL LEAST SQUARES PROBLEMS

  • Lee, Geunseop
    • Journal of the Korean Mathematical Society
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    • v.54 no.5
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    • pp.1557-1571
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    • 2017
  • The L-curve method is a parametric plot of interrelation between the residual norm of the least squares problem and the solution norm. However, the L-curve method may be hard to apply to the total least squares problem due to its no closed form solution of the regularized total least squares problems. Thus the sequence of the solution norm under the fixed regularization parameter and its corresponding residual need to be found with an efficient manner. In this paper, we suggest an efficient algorithm to find the sequence of the solutions and its residual in order to plot the L-curve for the total least squares problems. In the numerical experiments, we present that the proposed algorithm successfully and efficiently plots fairly 'L' like shape for some practical regularized total least squares problems.

A SPLIT LEAST-SQUARES CHARACTERISTIC MIXED FINITE ELEMENT METHOD FOR THE CONVECTION DOMINATED SOBOLEV EQUATIONS

  • OHM, MI RAY;SHIN, JUN YONG
    • Journal of applied mathematics & informatics
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    • v.34 no.1_2
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    • pp.19-34
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    • 2016
  • In this paper, we present a split least-squares characteristic mixed finite element method(MFEM) to get the approximate solutions of the convection dominated Sobolev equations. First, to manage both convection term and time derivative term efficiently, we apply a least-squares characteristic MFEM to get the system of equations in the primal unknown and the flux unknown. Then, we obtain a split least-squares characteristic MFEM to convert the coupled system in two unknowns derived from the least-squares characteristic MFEM into two uncoupled systems in the unknowns. We theoretically prove that the approximations constructed by the split least-squares characteristic MFEM converge with the optimal order in L2 and H1 normed spaces for the primal unknown and with the optimal order in L2 normed space for the flux unknown. And we provide some numerical results to confirm the validity of our theoretical results.

Least-Squares Meshfree Method and Integration Error (최소 제곱 무요소법과 적분 오차)

  • Park, Sang-Hun;Yun, Seong-Gi
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.10
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    • pp.1605-1612
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    • 2001
  • Least-squares meshfree method is presented. Conventional meshfree methods based on the Galerkin formulation suffer from inaccurate numerical integration. Least-squares formulation exhibits rather different integration-related characteristics. It is demonstrated through numerical examples that least-squares formulation is much more robust to integration errors than the Galerkin's. Therefore efficient meshfree methods can be devised by combining very simple integration algorithms and least-squares formulation.

LEAST-SQUARES SPECTRAL COLLOCATION PARALLEL METHODS FOR PARABOLIC PROBLEMS

  • SEO, JEONG-KWEON;SHIN, BYEONG-CHUN
    • Honam Mathematical Journal
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    • v.37 no.3
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    • pp.299-315
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    • 2015
  • In this paper, we study the first-order system least-squares (FOSLS) spectral method for parabolic partial differential equations. There were lots of least-squares approaches to solve elliptic partial differential equations using finite element approximation. Also, some approaches using spectral methods have been studied in recent. In order to solve the parabolic partial differential equations in parallel, we consider a parallel numerical method based on a hybrid method of the frequency-domain method and first-order system least-squares method. First, we transform the parabolic problem in the space-time domain to the elliptic problems in the space-frequency domain. Second, we solve each elliptic problem in parallel for some frequencies using the first-order system least-squares method. And then we take the discrete inverse Fourier transforms in order to obtain the approximate solution in the space-time domain. We will introduce such a hybrid method and then present a numerical experiment.

A SPLIT LEAST-SQUARES CHARACTERISTIC MIXED ELEMENT METHOD FOR SOBOLEV EQUATIONS WITH A CONVECTION TERM

  • Ohm, Mi Ray;Shin, Jun Yong
    • East Asian mathematical journal
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    • v.35 no.5
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    • pp.569-587
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    • 2019
  • In this paper, we consider a split least-squares characteristic mixed element method for Sobolev equations with a convection term. First, to manipulate both convection term and time derivative term efficiently, we apply a characteristic mixed element method to get the system of equations in the primal unknown and the flux unknown and then get a least-squares minimization problem and a least-squares characteristic mixed element scheme. Finally, we obtain a split least-squares characteristic mixed element scheme for the given problem whose system is uncoupled in the unknowns. We prove the optimal order in $L^2$ and $H^1$ normed spaces for the primal unknown and the suboptimal order in $L^2$ normed space for the flux unknown.

The Least-Squares Meshfree Method for the Analysis of Rigid-Plastic Deformation (강소성 변형 해석을 위한 최소 제곱 무요소법)

  • 윤성기;권기찬
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.12
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    • pp.2019-2031
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    • 2004
  • The least-squares formulation for rigid-plasticity based on J$_2$-flow rule and infinitesimal theory and its meshfree implementation using moving least-squares approximation are proposed. In the least-squares formulation the squared residuals of the constitutive and equilibrium equations are minimized. Those residuals are represented in a form of first-order differential system using the velocity and stress components as independent variables. For the enforcement of the boundary and frictional contact conditions, penalty scheme is employed. Also the reshaping of nodal supports is introduced to avoid the difficulties due to the severe local deformation near the contact interface. The proposed least-squares meshfree method does not require any structure of extrinsic cells during the whole process of analysis. Through some numerical examples of metal forming processes, the validity and effectiveness of the method are investigated.

A HIGHER ORDER SPLIT LEAST-SQUARES CHARACTERISTIC MIXED ELEMENT METHOD FOR SOBOLEV EQUATIONS

  • Ohm, Mi Ray;Shin, Jun Yong
    • East Asian mathematical journal
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    • v.38 no.3
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    • pp.293-319
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    • 2022
  • In this paper, we introduce a higher order split least-squares characteristic mixed element scheme for Sobolev equations. First, we use a characteristic mixed element method to manipulate both convection term and time derivative term efficiently and obtain the system of equations in the primal unknown and the flux unknown. Second, we define a least-squares minimization problem and a least-squares characteristic mixed element scheme. Finally, we obtain a split least-squares characteristic mixed element scheme for the given problem whose system is uncoupled in the unknowns. We establish the convergence results for the primal unknown and the flux unknown with the second order in a time increment.

Simplification of Linear Time-Invariant Systems by Least Squares Method (최소자승법을 이용한 선형시불변시스템의 간소화)

  • 추연석;문환영
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.5
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    • pp.339-344
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    • 2000
  • This paper is concerned with the simplification of complex linear time-invariant systems. A simple technique is suggested using the well-known least squares method in the frequency domain. Given a high-order transfer function in the s- or z-domain, the squared-gain function corresponding to a low-order model is computed by the least squares method. Then, the low-order transfer function is obtained through the factorization. Three examples are given to illustrate the efficiency of the proposed method.

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Asymmetric least squares regression estimation using weighted least squares support vector machine

  • Hwan, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.5
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    • pp.999-1005
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    • 2011
  • This paper proposes a weighted least squares support vector machine for asymmetric least squares regression. This method achieves nonlinear prediction power, while making no assumption on the underlying probability distributions. The cross validation function is introduced to choose optimal hyperparameters in the procedure. Experimental results are then presented which indicate the performance of the proposed model.

A Note on Estimating Parameters in The Two-Parameter Weibull Distribution

  • Rahman, Mezbahur;Pearson, Larry M.
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.1091-1102
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    • 2003
  • The Weibull variate is commonly used as a lifetime distribution in reliability applications. Estimation of parameters is revisited in the two-parameter Weibull distribution. The method of product spacings, the method of quantile estimates and the method of least squares are applied to this distribution. A comparative study between a simple minded estimate, the maximum likelihood estimate, the product spacings estimate, the quantile estimate, the least squares estimate, and the adjusted least squares estimate is presented.

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