Gas mixtures IR absorption spectra decomposition using a deep neural network
An approach to multicomponent gas mixtures IR absorption spectra decomposition using a deep neu- ral network was developed. The process of refinement and optimization of the absorption spectra data model to improve the accuracy of the inverse spectroscopic task solution is described. A criterion for...
| Published in: | Journal of Quantitative Spectroscopy and Radiative Transfer Vol. 301. P. 108521 (1-10) |
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| Other Authors: | , , , |
| Format: | Article |
| Language: | English |
| Subjects: | |
| Online Access: | http://vital.lib.tsu.ru/vital/access/manager/Repository/koha:001016660 |
| Summary: | An approach to multicomponent gas mixtures IR absorption spectra decomposition using a deep neu- ral network was developed. The process of refinement and optimization of the absorption spectra data model to improve the accuracy of the inverse spectroscopic task solution is described. A criterion for the reliability of restoring the concentration of an individual component in a gas mixture based on its share of the area under the absorption spectrum curve was suggested and tested. |
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| Bibliography: | Библиогр.: 40 назв. |
| ISSN: | 0022-4073 |