• Title/Summary/Keyword: least squares problem

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Extended MLS Difference Method for Potential Problem with Weak and Strong Discontinuities (복합 불연속면을 갖는 포텐셜 문제 해석을 위한 확장된 MLS 차분법)

  • Yoon, Young-Cheol;Noh, Hyuk-Chun
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.24 no.5
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    • pp.577-588
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    • 2011
  • This paper provides a novel extended Moving Least Squares(MLS) difference method for the potential problem with weak and strong discontinuities. The conventional MLS difference method is enhanced with jump functions such as step function, wedge function and scissors function to model discontinuities in the solution and the derivative fields. When discretizing the governing equations, additional unknowns are not yielded because the jump functions are decided from the known interface condition. The Poisson type PDE's are discretized by the difference equations constructed on nodes. The system of equations built up by assembling the difference equations are directly solved, which is very efficient. Numerical examples show the excellence of the proposed numerical method. The method is expected to be applied to various discontinuity related problems such as crack problem, moving boundary problem and interaction problems.

Development of Nonlinear Programming Approaches to Large Scale Linear Programming Problems (비선형계획법을 이용한 대규모 선형계획해법의 개발)

  • Chang, Soo-Y.
    • Journal of Korean Institute of Industrial Engineers
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    • v.17 no.2
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    • pp.131-142
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    • 1991
  • The concept of criterion function is proposed as a framework for comparing the geometric and computational characteristics of various nonlinear programming approaches to linear programming such as the method of centers, Karmakar's algorithm and the gravitational method. Also, we discuss various computational issues involved in obtaining an efficient parallel implementation of these methods. Clearly, the most time consuming part in solving a linear programming problem is the direction finding procedure, where we obtain an improving direction. In most cases, finding an improving direction is equivalent to solving a simple optimization problem defined at the current feasible solution. Again, this simple optimization problem can be seen as a least squares problem, and the computational effort in solving the least squares problem is, in fact, same as the effort as in solving a system of linear equations. Hence, getting a solution to a system of linear equations fast is very important in solving a linear programming problem efficiently. For solving system of linear equations on parallel computing machines, an iterative method seems more adequate than direct methods. Therefore, we propose one possible strategy for getting an efficient parallel implementation of an iterative method for solving a system of equations and present the summary of computational experiment performed on transputer based parallel computing board installed on IBM PC.

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Minimum Zone Evaluation of Straightness Using the Genius Education Concept (영재 교육 개념을 응용한 직선도의 최소영역 평가)

  • Kim, Soo-Kwang;Cho, Dong-Woo;Lee, Kahng-In
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.8
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    • pp.130-137
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    • 1999
  • The criteria for determining the elements are the minimum zone method(MZM) and the least squares method(LSM). The LSM is deterministic and simple but is limited at the measurements whose errors are significant compared with form errors. For the precise condition, minimum zone method(MZM) has been selected to determine the elements. It is not deterministic and nonlinear so that a optimizing procedure is needed. The Straightness is the fundamental problem in the evaluating form error. In this paper, a new approach adapting the genius education concept is proposed to obtain an accurate results for the minimum zone problem of the straightness. Its computational algorithm is studied on a set of randomly generated data. To be of almost no account of the specification(the number and the standard devistion etc.) of the sample data, the results shows excellent reliability and high accuracy in estimating the straightness.

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Meshless equilibrium on line method (MELM) for linear elasticity

  • Sadeghirad, A.;Mohammadi, S.;Kani, I. Mahmoudzadeh
    • Structural Engineering and Mechanics
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    • v.35 no.4
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    • pp.511-533
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    • 2010
  • As a truly meshfree method, meshless equilibrium on line method (MELM), for 2D elasticity problems is presented. In MELM, the problem domain is represented by a set of distributed nodes, and equilibrium is satisfied on lines for any node within this domain. In contrary to conventional meshfree methods, test domains are lines in this method, and all integrals can be easily evaluated over straight lines along x and y directions. Proposed weak formulation has the same concept as the equilibrium on line method which was previously used by the authors for enforcement of the Neumann boundary conditions in the strong-form meshless methods. In this paper, the idea of the equilibrium on line method is developed to use as the weak forms of the governing equations at inner nodes of the problem domain. The moving least squares (MLS) approximation is used to interpolate solution variables in this paper. Numerical studies have shown that this method is simple to implement, while leading to accurate results.

AN ALGORITHM FOR FITTING OF SPHERES

  • Kim, Ik-Sung
    • The Pure and Applied Mathematics
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    • v.11 no.1
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    • pp.37-49
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    • 2004
  • We are interested in the problem of fitting a sphere to a set of data points in the three dimensional Euclidean space. In Spath [6] a descent algorithm already have been given to find the sphere of best fit in least squares sense of minimizing the orthogonal distances to the given data points. In this paper we present another new algorithm which computes a parametric represented sphere in order to minimize the sum of the squares of the distances to the given points. For any choice of initial approximations our algorithm has the advantage of ensuring convergence to a local minimum. Numerical examples are given.

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Analysis of Stress Concentration Problems Using Moving Least Squares Finite Difference Method(II) : Application to crack and localization band problems (이동최소제곱 유한차분법을 이용한 응력집중문제 해석(II) : 균열과 국소화 밴드 문제로의 적용)

  • Yoon, Young-Cheol;Kim, Hyo-Jin;Kim, Dong-Jo;Liu, Wing Kam;Belytschko, Ted;Lee, Sang-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.20 no.4
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    • pp.501-507
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    • 2007
  • In the first part of this study, the moving least squares finite difference method for solving solid mechanics problems was formulated. This second part verified the accuracy, robustness and effectiveness of the developed method through several numerical examples. It was shown that the method gives excellent convergence rate for elasticity problem. The solution process of elastic crack problems showed the easiness in discontinuity modeling and demonstrates the accuracy and efficiency in finding singular stress solution based on adaptive node distribution. The applicability to the engineering problem with abrupt change in displacement and stresses gradient fields is verified through a localization band problem. The developed method is expected to be extended to the various special engineering problems.

Forecast and Demand Analysis of Oyster as Kimchi's Ingredients (김장굴의 수요 분석 및 예측)

  • Nam, Jong-Oh;Nho, Seung-Guk
    • The Journal of Fisheries Business Administration
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    • v.42 no.2
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    • pp.69-83
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    • 2011
  • This paper estimates demand functions of oyster as Kimchi's ingredients of capital area, other areas excluding a capital area, and a whole area in Korea to forecast its demand quantities in 2011~2015. To estimate oyster demand function, this paper uses pooled data produced from Korean housewives over 30 years old in 2009 and 2010. Also, this paper adopts several econometrics methods such as Ordinary Least Squares and Feasible Generalized Least Squares. First of all, to choose appropriate variables of oyster demand functions by area, this paper carries out model's specification with joint significance test. Secondly, to remedy heteroscedasticity with pooled data, this paper attempts residual plotting between estimated squared residuals and estimated dependent variable and then, if it happens, undertakes White test to care the problem. Thirdly, to test multicollinearity between variables with pooled data, this paper checks correlations between variables by area. In this analysis, oyster demand functions of a capital area and a whole area need price of the oyster, price of the cabbage for Gimjang, and income as independent variables. The function on other areas excluding a capital area only needs price of the oyster and income as ones. In addition, the oyster demand function of a whole area needed White test to care a heteroscedasticity problem and demand functions of the other two regions did not have the problem. Thus, first model was estimated by FGLS and second two models were carried out by OLS. The results suggest that oyster demand quantities per a household as Kimchi's ingredients are going to slightly increase in a capital area and a whole area, but slightly decrease in other areas excluding a capital area in 2011~2015. Also, the results show that oyster demand quantities as kimchi's ingredients for total household targeting housewives over 30 years old are going to slightly increase in three areas in 2011~2015.

ROBUST TEST BASED ON NONLINEAR REGRESSION QUANTILE ESTIMATORS

  • CHOI, SEUNG-HOE;KIM, KYUNG-JOONG;LEE, MYUNG-SOOK
    • Communications of the Korean Mathematical Society
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    • v.20 no.1
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    • pp.145-159
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    • 2005
  • In this paper we consider the problem of testing statistical hypotheses for unknown parameters in nonlinear regression models and propose three asymptotically equivalent tests based on regression quantiles estimators, which are Wald test, Lagrange Multiplier test and Likelihood Ratio test. We also derive the asymptotic distributions of the three test statistics both under the null hypotheses and under a sequence of local alternatives and verify that the asymptotic relative efficiency of the proposed test statistics with classical test based on least squares depends on the error distributions of the regression models. We give some examples to illustrate that the test based on the regression quantiles estimators performs better than the test based on the least squares estimators of the least absolute deviation estimators when the disturbance has asymmetric and heavy-tailed distribution.

Local Minimum Problem of the ILS Method for Localizing the Nodes in the Wireless Sensor Network and the Clue (무선센서네트워크에서 노드의 위치추정을 위한 반복최소자승법의 지역최소 문제점 및 이에 대한 해결책)

  • Cho, Seong-Yun
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.10
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    • pp.1059-1066
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    • 2011
  • This paper makes a close inquiry into ill-conditioning that may be occurred in wireless localization of the sensor nodes based on network signals in the wireless sensor network and provides the clue for solving the problem. In order to estimate the location of a node based on the range information calculated using the signal propagation time, LS (Least Squares) method is usually used. The LS method estimates the solution that makes the squared estimation error minimal. When a nonlinear function is used for the wireless localization, ILS (Iterative Least Squares) method is used. The ILS method process the LS method iteratively after linearizing the nonlinear function at the initial nominal point. This method, however, has a problem that the final solution may converge into a LM (Local Minimum) instead of a GM (Global Minimum) according to the deployment of the fixed nodes and the initial nominal point. The conditions that cause the problem are explained and an adaptive method is presented to solve it, in this paper. It can be expected that the stable location solution can be provided in implementation of the wireless localization methods based on the results of this paper.