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Performance of Differential Evolution Method in Least Squares Fitting of Some Typical Nonlinear Curves Author info | Abstract | Publisher info | Download info | Related research | Statistics Mishra, SK
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No foolproof method exists to fit nonlinear curves to data or estimate the parameters of an intrinsically nonlinear function. Some methods succeed at solving a set of problems but fail at the others. The Differential Evolution (DE) method of global optimization is an upcoming method that has shown its power to solve difficult nonlinear optimization problems. In this study we use the DE to solve some nonlinear least squares problems given by the National Institute of Standards and Technology (NIST), US Department of Commerce, USA and some other challenge problems posed by the CPC-X Software (the makers of the AUTO2FIT software). The DE solves the test problems given by the NIST and most of the challenge problems posed by the CPC-X, doing marginally better than the AUTO2FIT software in a few cases.
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number
4634.
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Date of creation: 29 Aug 2007Date of revision:
31 Aug 2007Handle: RePEc:pra:mprapa:4634Contact details of provider: Postal: Schackstr. 4, D-80539 Munich, Germany Phone: +49-(0)89-2180-2219 Fax: +49-(0)89-2180-3900 Web page: http://mpra.ub.uni-muenchen.de More information through EDIRC
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Keywords: Nonlinear least squares curve fitting Differential Evolution global optimization AUTO2FIT CPC-X Software NIST National Institute of Standards and Technology test problems Other versions of this item:
Find related papers by JEL classification: C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
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