Inversion of oceanic constituents in case I and II waters with genetic programming algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{2002ApOpt..41.6260C,

• author = "Malik Chami and Denis Robilliard",
• title = "Inversion of oceanic constituents in case {I} and {II} waters with genetic programming algorithms",
• year = "2002",
• month = "20 " # oct,
• volume = "41",
• pages = "6260--6275",
• journal = "Applied Optics",
• number = "30",
• adsurl = "http://adsabs.harvard.edu/cgi-bin/nph-bib_query?bibcode=2002ApOpt..41.6260C&db_key=INST",
• adsnote = "Provided by the NASA Astrophysics Data System",
• keywords = "genetic algorithms, genetic programming, ARTIFICIAL SATELLITES, ATMOSPHERIC OPTICS, COLOUR, INFRARED SPECTROSCOPY, LIGHT TRANSMISSION, OPTICAL PROPERTIES, RADIATIVE TRANSFER, REFLECTANCE, REMOTE SENSING, SEA WATER, SPECTROSCOPIC ANALYSIS, STOCHASTIC PROCESSES, WAVE PROPAGATION",
• ISSN = "1559-128X",
• URL = "http://ao.osa.org/ViewMedia.cfm?id=70258&seq=0",
• DOI = "doi:10.1364/AO.41.006260",
• size = "16 pages",
• abstract = "A stochastic inverse technique based on a genetic programming (GP) algorithm was developed to invert oceanic constituents from simulated data for case I and case II water applications. The simulations were carried out with the Ordre Successifs Ocean Atmosphere (OSOA) radiative transfer model. They include the effects of oceanic substances such as algal-related chlorophyll, nonchlorophyllous suspended matter, and dissolved organic matter. The synthetic data set also takes into account the directional effects of particles through a variation of their phase function that makes the simulated data realistic. It is shown that GP can be successfully applied to the inverse problem with acceptable stability in the presence of realistic noise in the data. GP is compared with neural network methodology for case I waters; GP exhibits similar retrieval accuracy, which is greater than for traditional techniques such as band ratio algorithms. The application of GP to real satellite data [a Sea-viewing Wide Field-of-view Sensor (SeaWiFS)] was also carried out for case I waters as a validation. Good agreement was obtained when GP results were compared with the SeaWiFS empirical algorithm. For case II waters the accuracy of GP is less than 33percent, which remains satisfactory, at the present time, for remote-sensing purposes.",
• notes = "http://adsabs.harvard.edu/cgi-bin/nph-bib_query?bibcode=2002ApOpt..41.6260C&data_type=BIBTEX&db_key=INST%26amp;nocookieset=1",

}

Genetic Programming entries for Malik Chami Denis Robilliard

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