Solving the ocean color problem using a genetic programming approach
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- @Article{fonlupt:2001:ASC,
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author = "C. Fonlupt",
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title = "Solving the ocean color problem using a genetic
programming approach",
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journal = "Applied Soft Computing",
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year = "2001",
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volume = "1",
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number = "1",
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pages = "63--72",
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month = jun,
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keywords = "genetic algorithms, genetic programming, Ocean colour
problem, Phytoplankton",
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URL = "http://www.sciencedirect.com/science/article/B6W86-43S6W98-6/2/ed66cf73aec7cb186639405e4a8801bb",
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DOI = "doi:10.1016/S1568-4946(01)00007-2",
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abstract = "The ocean color problem consists in evaluating ocean
components concentrations (phytoplankton, sediment and
yellow substance) from sunlight reflectance or
luminance values at selected wavelengths in the visible
band. The interest of this application increases with
the availability of new satellite sensors. Moreover,
monitoring phytoplankton concentrations is a key point
for a wide set of problems ranging from greenhouse
effect to industrial fishing and signaling toxic algae
blooms. To our knowledge, it is the first attempt at
this regression problem with genetic programming (GP).
We show that GP outperforms traditional polynomial fits
and rivals artificial neural nets in the case of open
ocean waters. We improve previous works by also solving
a range of coastal waters types, providing detailed
results on estimation errors. To our knowledge, we are
the firsts to publish numerical results regarding
coastal waters. Experiments were conducted with a
dynamic fitness GP algorithm in order to speed up
computing time through a process of progressive
learning.",
- }
Genetic Programming entries for
Cyril Fonlupt
Citations