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Proceedings Paper

Algorithms of self-adaptation for atmospheric model designing
Author(s): Juliy P. Lankin; Tatyana F. Baskanova
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Paper Abstract

The paper describes the principal limitations of the traditional methods used to construct atmospheric models. These limitations would not allow any fundamental improvement of atmospheric modeling. Ways are proposed to overcome the current limitations, based on teh methodology of constructing adaptive models and neuroinformatics. Algorithms of self-adaptation for neural networks intended for the construction of atmospheric models are given. Essentially, the developed algorithms are adaptive shells and can be easily transferred to other models.

Paper Details

Date Published: 23 February 2004
PDF: 11 pages
Proc. SPIE 5397, Tenth Joint International Symposium on Atmospheric and Ocean Optics/Atmospheric Physics. Part II: Laser Sensing and Atmospheric Physics, (23 February 2004); doi: 10.1117/12.548609
Show Author Affiliations
Juliy P. Lankin, Institute of Biophysics (Russia)
Tatyana F. Baskanova, Krasnoyarsk State Univ. (Russia)


Published in SPIE Proceedings Vol. 5397:
Tenth Joint International Symposium on Atmospheric and Ocean Optics/Atmospheric Physics. Part II: Laser Sensing and Atmospheric Physics
Gennadii G. Matvienko; Georgii M. Krekov, Editor(s)

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