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Applied Optics

Applied Optics


  • Vol. 40, Iss. 3 — Jan. 20, 2001
  • pp: 331–335

Spectral radiative-transfer modeling with minimized computation time by use of a neural-network technique

Harry Schwander, Anton Kaifel, Ansgar Ruggaber, and Peter Koepke  »View Author Affiliations

Applied Optics, Vol. 40, Issue 3, pp. 331-335 (2001)

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A new approach based on a neural-network technique for reduction in the computation time of radiative-transfer models is presented. This approach gives high spectral resolution without significant loss of accuracy. A rigorous radiative-transfer model is used to calculate radiation values at a few selected wavelengths, and a neural-network algorithm replenishes them to a complete spectrum with radiation values at a high spectral resolution. This method is used for the UV and visible spectral ranges. The results document the ability of a neural network to learn this specific task. More than 20,000 UV-index values for all kinds of atmosphere are calculated by both the rigorous radiative-transfer model alone and the model in combination with the neural-network algorithm. The agreement between both approaches is generally of the order of ±1%; the computation time is reduced by a factor of more than 20. The new algorithm can be used for all kinds of high-quality radiative-transfer model to speed up computation time.

© 2001 Optical Society of America

OCIS Codes
(010.1320) Atmospheric and oceanic optics : Atmospheric transmittance
(030.5620) Coherence and statistical optics : Radiative transfer
(040.7190) Detectors : Ultraviolet
(200.4260) Optics in computing : Neural networks

Original Manuscript: February 16, 2000
Revised Manuscript: September 29, 2000
Published: January 20, 2001

Harry Schwander, Anton Kaifel, Ansgar Ruggaber, and Peter Koepke, "Spectral radiative-transfer modeling with minimized computation time by use of a neural-network technique," Appl. Opt. 40, 331-335 (2001)

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