Symbolic and numerical regression: Experiments and applications
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{davidson:2003:IS,
-
author = "J. W. Davidson and D. A. Savic and G. A. Walters",
-
title = "Symbolic and numerical regression: Experiments and
applications",
-
journal = "Information Sciences",
-
year = "2003",
-
volume = "150",
-
pages = "95--117",
-
number = "1-2",
-
DOI = "doi:10.1016/S0020-0255(02)00371-7",
-
URL = "http://www.sciencedirect.com/science/article/B6V0C-474DD2V-1/2/3368220198ea15f93a793594af73d8d1",
-
keywords = "genetic algorithms, genetic programming, Least
squares, Rule-based programming, Stepwise regression,
Symbolic regression",
-
abstract = "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.",
- }
Genetic Programming entries for
J W Davidson
Dragan Savic
Godfrey A Walters
Citations