Iterative Filter Generation Using Genetic Programming

  • Marc Segond
  • Denis Robilliard
  • Cyril Fonlupt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3905)


Oceanographers from the IFREMER institute have an hypothesis that the presence of so-called “retentive” meso-scale vortices in ocean and coastal waters could have an influence on watery fauna’s demography. Up to now, identification of retentive hydro-dynamical structures on stream maps has been performed by experts using background knowledge about the area. We tackle this task with filters induced by Genetic Programming, a technique that has already been successfully used in pattern matching problems. To overcome specific difficulties associated with this problem, we introduce a refined scheme that iterates the filters classification phase while giving them access to a memory of their previous decisions. These iterative filters achieve superior results and are compared to a set of other methods.


Genetic Program Vortex Detection Pattern Match Problem Iterative Filter Computer Assist Design 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Marc Segond
    • 1
  • Denis Robilliard
    • 1
  • Cyril Fonlupt
    • 1
  1. 1.Laboratoire d’Informatique du Littoral, Maison de la Recherche Blaise PascalCALAISFrance

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