Linear Regression Models and Neural Networks for the Fast Emulation of a Molecular Absorption Code
| Autor: | Guillaume Euvrard, Sidonie Lefebvre, Pierre Simoneau, Thierry Huet, Isabelle Rivals |
|---|---|
| Přispěvatelé: | Equipe de Statistique Appliquée (UMRS 1158) (ESA), Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Neurophysiologie Respiratoire Expérimentale et Clinique, Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), ONERA - The French Aerospace Lab [Châtillon], ONERA-Université Paris Saclay (COmUE) |
| Jazyk: | angličtina |
| Rok vydání: | 2009 |
| Předmět: |
0209 industrial biotechnology
010504 meteorology & atmospheric sciences Absorption spectroscopy Computer science Materials Science (miscellaneous) Computation 02 engineering and technology Numerical approximation and analysis [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE] 01 natural sciences Industrial and Manufacturing Engineering Image (mathematics) Absorption Set (abstract data type) 020901 industrial engineering & automation Optics [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Linear regression Radiative transfer Business and International Management 0105 earth and related environmental sciences Emulation 000.4430 010.1030 010.5620 200.4260 010.1300 Artificial neural network Atmospheric propagation 110.2960 Image analysis business.industry [INFO.INFO-NA]Computer Science [cs]/Numerical Analysis [cs.NA] Radiance business Algorithm Nonlinear regression [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing Molecular absorption Neural networks Generator (mathematics) |
| Zdroj: | Applied optics Applied optics, Optical Society of America, 2009, 48 (35), pp.6770-6780 |
| ISSN: | 0003-6935 1539-4522 |
| Popis: | International audience; The background scene generator MATISSE, whose main functionality is to generate natural background radiance images, makes use of the so-called Correlated K (CK) model. It necessitates either to load or to compute thousands of CK coefficients for each atmospheric profile. When the CK coefficients cannot be loaded, the computation time becomes prohibitive. The idea developed in this paper is to substitute fast approximate models to the exact CK generator: using the latter, a representative set of numerical examples is built and used to train linear or nonlinear regression models. The resulting models enable an accurate CK coefficient computation for all the profiles of an image in a reasonable time. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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