Abstract
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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Segond, M., Robilliard, D., Fonlupt, C. (2006). Iterative Filter Generation Using Genetic Programming. In: Collet, P., Tomassini, M., Ebner, M., Gustafson, S., Ekárt, A. (eds) Genetic Programming. EuroGP 2006. Lecture Notes in Computer Science, vol 3905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11729976_13
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DOI: https://doi.org/10.1007/11729976_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33143-8
Online ISBN: 978-3-540-33144-5
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