Symbolic and numerical regression: experiments and applications

This paper describes a new method for creating polynomial regression models. The new method is compared with stepwise regression and symbolic regression using three example problems. The first example is a polynomial equation. The two examples that follow are real-world problems, approximating the C...

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Vydáno v:	Information sciences Ročník 150; číslo 1; s. 95 - 117
Hlavní autoři:	Davidson, J.W., Savic, D.A., Walters, G.A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Inc 01.03.2003
Témata:	Genetic programming Least squares Rule-based programming Stepwise regression Symbolic regression Symbolic regression Rule-based programming Stepwise regression Genetic programming Least squares
ISSN:	0020-0255, 1872-6291
On-line přístup:	Získat plný text
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Popis
Shrnutí:	This paper describes a new method for creating polynomial regression models. The new method is compared with stepwise regression and symbolic regression using three example problems. The first example is a polynomial equation. The two examples that follow are real-world problems, approximating the Colebrook–White equation and rainfall-runoff modelling. The three example problems illustrate the advantages of the new method.
ISSN:	0020-0255 1872-6291
DOI:	10.1016/S0020-0255(02)00371-7