Application of artificial neural networks for determining the temperature and partial pressures of the components of high-temperature gaseous media

doi:10.1109/EFRE47760.2020.9241969

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Application of artificial neural networks for determining the temperature and partial pressures of the components of high-temperature gaseous media	150 KB	Adobe Acrobat PDF	Read	Download
DOI Доступ к ресурсу на сайте издателя			10.1109/EFRE47760.2020.9241969

#искусственный нейронные сети

#коэффициент пропускания

#высокотемпературная газовая среда

#температура

#парциальное давление

Title: Application of artificial neural networks for determining the temperature and partial pressures of the components of high-temperature gaseous media
Creator: Kashirskii, Danila E.
Date: 2020
DOI: 10.1109/EFRE47760.2020.9241969
Description: The paper deals with the development of methods for solving the inverse problem of gaseous media optics by determining the parameters of high-temperature gaseous media from its spectral characteristics. It is proposed to use artificial neural networks to determine the temperature and partial pressures of water vapor, carbon dioxide, carbon oxide and nitrogen oxide from its transmissivities.

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collection(s): Радиофизический факультет
Identifier: смотреть в электронном каталоге НБ ТГУ
Type: статьи в сборниках
Source: 2020 7th International Congress on energy fluxes and radiation effects (EFRE 2020), Tomsk, Russia, September 14 – 26, 2020 : proceedings. [S. l.], 2020. P. 1045-1047
Language: eng

Created: 22-04-2021

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Радиофизический факультет Application of artificial neural networks for determining the temperature and partial pressures of the components of high-temperature gaseous media