A new algorithm for estimation of parameter of nonlinear regression modeling
type: Item
instance of: scholarly article
zbMATH Open document ID: 0997.93026
author: Jinshan Chen
author: Gang Wei
publication date: 2002-05-21T00:00:00Z
Mathematics Subject Classification ID: 93B30
Mathematics Subject Classification ID: 93C10
zbMATH DE Number: 1695308
zbMATH Keywords: nonlinear parameter estimation
zbMATH Keywords: genetic algorithm
zbMATH Keywords: least squares estimation
zbMATH Keywords: identification
MaRDI profile type: Publication
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title: A new algorithm for estimation of parameter of nonlinear regression modeling
published in: Control Theory \& Applications
review text: The authors consider an identification problem for estimating the parameter vector in a nonlinear regression model. They first reduce the above estimation problem to minimizing a nonlinear least squares cost functional and then propose a hybrid genetic algorithm to solve the above optimization problem. The proposed algorithm can rapidly converge to the global optima by performing global searches and local searches alternatively in the parameter space. The simulation example is given to illustrate the general use and the effectiveness of their algorithm.
reviewed by: Yu Wenhuan
description: scientific article; zbMATH DE number 1695308