- author = "Gregory Valigiani and Cyril Fonlupt and Pierre Collet",
- title = "Analysis of GP Improvement Techniques over the Real-World Inverse Problem of Ocean Color",
- booktitle = "Genetic Programming 7th European Conference, EuroGP 2004, Proceedings",
- year = "2004",
- editor = "Maarten Keijzer and Una-May O'Reilly and Simon M. Lucas and Ernesto Costa and Terence Soule",
- volume = "3003",
- series = "LNCS",
- pages = "174--186",
- address = "Coimbra, Portugal",
- publisher_address = "Berlin",
- month = "5-7 " # apr,
- organisation = "EvoNet",
- publisher = "Springer-Verlag",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "3-540-21346-5",
-
DOI = "
doi:10.1007/978-3-540-24650-3_16",
-
abstract = "This paper is a follow-up of Maarten Keijzer's
award-winning EUROGP'03 paper [\cite{keijzer03}], that
suggests using Interval Arithmetic (IA) and Linear
Scaling (LS) in Genetic Programming algorithms. The
ideas exposed in this paper were so nice that it was
decided to experiment with them on a real-world problem
on which the LIL research team had some experience and
results with: the Ocean Colour Inverse Problem.
After extensive testing of IA, LS as well as a progressive learning method using thresholds (T), results seem to show that functions evolved with GP algorithms that do not implement IA may output erroneous values outside the learning set, while LS and T methods produce solutions with a greater generalisation error.
A simple and apparently harmless improvement over standard GP is also proposed, that consists in weighting operands of + and - operators.",
- notes = "Part of \cite{keijzer:2004:GP} EuroGP'2004 held in conjunction with EvoCOP2004 and EvoWorkshops2004",
