• Title/Summary/Keyword: least squares

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Thermal vibration analysis of thick laminated plates by the moving least squares differential quadrature method

  • Wu, Lanhe
    • Structural Engineering and Mechanics
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    • v.22 no.3
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    • pp.331-349
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    • 2006
  • The stresses and deflections in a laminated rectangular plate under thermal vibration are determined by using the moving least squares differential quadrature (MLSDQ) method based on the first order shear deformation theory. The weighting coefficients used in MLSDQ approximation are obtained through a fast computation of the MLS shape functions and their partial derivatives. By using this method, the governing differential equations are transformed into sets of linear homogeneous algebraic equations in terms of the displacement components at each discrete point. Boundary conditions are implemented through discrete grid points by constraining displacements, bending moments and rotations of the plate. Solving this set of algebraic equations yields the displacement components. Then substituting these displacements into the constitutive equation, we obtain the stresses. The approximate solutions for stress and deflection of laminated plate with cross layer under thermal load are obtained. Numerical results show that the MLSDQ method provides rapidly convergent and accurate solutions for calculating the stresses and deflections in a multi-layered plate of cross ply laminate subjected to thermal vibration of sinusoidal temperature including shear deformation with a few grid points.

Determination of Probable Rainfall Intensity Formulas for Designing Storm Sewer Systems at Incheon District (우수거 설계를 위한 인천지방에서의 확률강우강도식의 산정)

  • Ahn, Tae-Jin;Kim, Kyung-Sub
    • Journal of Korean Society of Water and Wastewater
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    • v.12 no.3
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    • pp.99-106
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    • 1998
  • This paper presents a procedure for determining the design rainfall depth and the design rainfall intensity at Incheon city area in Korea. In this study the eight probability distributions are considered to estimate the probable rainfall depths for 11 different durations. The Kolmogorov - Smirnov test and the Chi-square test are adopted to test each distribution. The probable rainfall intensity formulas are then determined by i) the least squares (LS) method, ii) the least median squares (LMS) method, iii) the reweighted least squares method based on the LMS (RLS), and iv) the constrained regression (CR) model. The Talbot, the Sherman, the Japanese, and the Unified type are considered to determine the best type for the Incheon station. The root mean squared (RMS) errors are computed to test the formulas derived by four methods. It is found that the Unified type is the most reliable and that all methods presented herein are acceptable for determining the coefficients of rainfall intensity formulas from an engineering point of view.

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An Accurate Estimation of a Modal System with Initial Conditions (ICCAS 2004)

  • Seo, In-Yong;Pearson, Allan E.
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1694-1700
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    • 2004
  • In this paper, we propose the AWLS/MFT (Adaptive Weighed Least Squares/ Modulation Function Technique) devised by A. E. Pearson et al. for the transfer function estimation of a modal system and investigate the performance of several algorithms, the Gram matrix method, a Luenberger Observer (LO), Least Squares (LS), and Recursive Least Squares (RLS), for the estimation of initial conditions. With the benefit of the Modulation Function Technique (MFT), we can separate the estimation problem into two phases: the transfer function parameters are estimated in the first phase, and the initial conditions are estimated in the second phase. The LO method produces excellent IC estimates in the noise free case, but the other three methods show better performance in the noisy case. Finally, we compared our result with the Prony based method. In the noisy case, the AWLS and one of the three methods - Gram matrix, LS, and RLS- show better performance in the output Signal to Error Ratio (SER) aspect than the Prony based method under the same simulation conditions.

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A New Recursive Least-Squares Algorithm based on Matrix Pseudo Inverses (ICCAS 2003)

  • Quan, Zhonghua;Han, Soo-Hee;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.927-931
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    • 2003
  • In this paper, a new Recursive Least-Squares(RLS) algorithm based on matrix pseudo-inverses is presented. The aim is to use the proposed new RLS algorithm for not only the over-determined but also the under-determined estimation problem. Compared with previous results, e.g., Jie Zhou et al., the derivation of the proposed recursive form is much easier, and the recursion form is also much simpler. Furthermore, it is shown by simulations that the proposed RLS algorithm is more efficient and numerically stable than the existing algorithms.

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Least Squares Velocity Estimation of a Mobile Robot Using a Regular Polygonal Array of Optical Mice (정다각형 배열의 광 마우스를 이용한 이동 로봇의 최소 자승 속도 추정)

  • Kim, Sung-Bok;Jeong, Il-Hwa;Lee, Sang-Hyup
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.10
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    • pp.978-982
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    • 2007
  • This paper presents the velocity estimation of a mobile robot using a regular polygonal array of optical mice that are installed at the bottom of a mobile robot. First, the basic principle of the proposed velocity estimation method is explained. Second, the velocity kinematics from a mobile robot to an array of optical mice is derived as an overdetermined linear system. Third, for a given set of optical mouse readings, the mobile robot velocity is estimated based on the least squares solution to the obtained system. Finally, simulation results are given to demonstrate the validity of the proposed velocity estimation method.

APPROXIMATE SOLUTIONS TO ONE-DIMENSIONAL BACKWARD HEAT CONDUCTION PROBLEM USING LEAST SQUARES SUPPORT VECTOR MACHINES

  • Wu, Ziku;Li, Fule;Kwak, Do Young
    • Journal of the Chungcheong Mathematical Society
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    • v.29 no.4
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    • pp.631-642
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    • 2016
  • This article deals with one-dimension backward heat conduction problem (BHCP). A new approach based on least squares support vector machines (LS-SVM) is proposed for obtaining their approximate solutions. The approximate solution is presented in closed form by means of LS-SVM, whose parameters are adjusted to minimize an appropriate error function. The approximate solution consists of two parts. The first part is a known function that satisfies initial and boundary conditions. The other is a product of two terms. One term is known function which has zero boundary and initial conditions, another term is unknown which is related to kernel functions. This method has been successfully tested on practical examples and has yielded higher accuracy and stable solutions.

Gas-liquid interface treatment in underwater explosion problem using moving least squares-smoothed particle hydrodynamics

  • Hashimoto, Gaku;Noguchi, Hirohisa
    • Interaction and multiscale mechanics
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    • v.1 no.2
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    • pp.251-278
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    • 2008
  • In this study, we investigate the discontinuous-derivative treatment at the gas-liquid interface in underwater explosion (UNDEX) problems by using the Moving Least Squares-Smoothed Particle Hydrodynamics (MLS-SPH) method, which is known as one of the particle methods suitable for problems where large deformation and inhomogeneity occur in the whole domain. Because the numerical oscillation of pressure arises from derivative discontinuity in the UNDEX analysis using the standard SPH method, the MLS shape function with Discontinuous-derivative Basis Function (DBF) that is able to represent the derivative discontinuity of field function is utilized in the MLS-SPH formulation in order to suppress the nonphysical pressure oscillation. The effectiveness of the MLS-SPH with DBF is demonstrated in comparison with the standard SPH and conventional MLS-SPH though a shock tube problem and benchmark standard problems of UNDEX of a trinitrotoluene (TNT) charge.

Determination of Minimum Eigenvalue in a Continuous-time Weighted Least Squares Estimator (연속시간 하중최소자승 식별기의 최소고우치 결정)

  • Kim, Sung-Duck
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.9
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    • pp.1021-1030
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    • 1992
  • When using a least squares estimator with exponential forgetting factor to identify continuous-time deterministic system, the problem of determining minimum eigenvalue is described in this paper. It is well known fact that the convergence rate of parameter estimates relies on various factors consisting of the estimator and especially, theirproperties can be directly affected by all eigenvalues in the parameter error differential equation. Fortunately, there exists only one adjusting eigenvalue in the given estimator and then, the parameter convergence rates depend on this minimum eigenvalue. In this note, a new result to determine the minimum eigenvalue is proposed. Under the assumption that the input has as many spectral lines as the number of parameter estimates, it can be proven that the minimum eigenvalue converges to a constant value, which is a function of the forgetting factor and the parameter estimates number.

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FINITE ELEMENT APPROXIMATION OF THE DISCRETE FIRST-ORDER SYSTEM LEAST SQUARES FOR ELLIPTIC PROBLEMS

  • SHIN, Byeong-Chun
    • Communications of the Korean Mathematical Society
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    • v.20 no.3
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    • pp.563-578
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    • 2005
  • In [Z. Cai and B. C. Shin, SIAM J. Numer. Anal. 40 (2002), 307-318], we developed the discrete first-order system least squares method for the second-order elliptic boundary value problem by directly approximating $H(div){\cap}H(curl)-type$ space based on the Helmholtz decomposition. Under general assumptions, error estimates were established in the $L^2\;and\;H^1$ norms for the vector and scalar variables, respectively. Such error estimates are optimal with respect to the required regularity of the solution. In this paper, we study solution methods for solving the system of linear equations arising from the discretization of variational formulation which possesses discrete biharmonic term and focus on numerical results including the performances of multigrid preconditioners and the finite element accuracy.

Software Reliability Assessment with Fuzzy Least Squares Support Vector Machine Regression

  • Hwang, Chang-Ha;Hong, Dug-Hun;Kim, Jang-Han
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.4
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    • pp.486-490
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    • 2003
  • Software qualify models can predict the risk of faults in the software early enough for cost-effective prevention of problems. This paper introduces a least squares support vector machine (LS-SVM) as a fuzzy regression method for predicting fault ranges in the software under development. This LS-SVM deals with the fuzzy data with crisp inputs and fuzzy output. Predicting the exact number of bugs in software is often not necessary. This LS-SVM can predict the interval that the number of faults of the program at each session falls into with a certain possibility. A case study on software reliability problem is used to illustrate the usefulness of this LS -SVM.