Analysis of GP Improvement Techniques over the Real-World Inverse Problem of Ocean Color

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{valigiani:2004:eurogp,
  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",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=3003&spage=174",
  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",
}

Genetic Programming entries for Gregory Valigiani Cyril Fonlupt Pierre Collet

Citations