Normal view
MARC view
Application of artificial neural networks for determining the temperature and partial pressures of the components of high-temperature gaseous media D. E. Kashirskii
Material type:
ArticleContent type: Текст Media type: электронный Subject(s): искусственный нейронные сети | коэффициент пропускания | высокотемпературная газовая среда | температура | парциальное давлениеGenre/Form: статьи в сборниках Online resources: Click here to access online
In:
2020 7th International Congress on energy fluxes and radiation effects (EFRE 2020), Tomsk, Russia, September 14 – 26, 2020 : proceedings P. 1045-1047Abstract: 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.
No physical items for this record
Библиогр.: 7 назв.
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.
There are no comments on this title.