DocumentCode
2546451
Title
A Genetic Algorithm for Spline Least Squares Calculations
Author
Jin, Wu
Author_Institution
Sch. of Comput. Sci. & Technol., Soochow Univ., Suzhou, China
fYear
2010
fDate
23-25 Sept. 2010
Firstpage
1
Lastpage
4
Abstract
In this paper we describe a method for least squares calculations with a spline function using a genetic algorithm (GA). Spline functions, which are piecewise polynomials, are the most successful approximating functions when their knots (the joining points) are considered as variables. This treatment results in a nonlinear least squares problem with many local minima. We apply the GA to search for the global minimum of the fitting criterion AIC (Akaike´s Information Criterion). A Numerical example is given.
Keywords
algorithm theory; genetic algorithms; piecewise polynomial techniques; splines (mathematics); genetic algorithm; nonlinear least squares problem; piecewise polynomials; spline function; spline least squares calculation; Biological cells; Fitting; Gallium; Genetic algorithms; Least squares approximation; Spline;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications Networking and Mobile Computing (WiCOM), 2010 6th International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-3708-5
Electronic_ISBN
978-1-4244-3709-2
Type
conf
DOI
10.1109/WICOM.2010.5600188
Filename
5600188
Link To Document