Application of Artificial Neural Networks for Determining the Temperature and Partial Pressures of the Components of High-Temperature Gaseous Media

摘要

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.