Using neural nets for reducing gas concentrations by the data of trass gas analyzer at CO2-laser; Bulletin of the Tomsk Polytechnic University; Vol. 311, № 5
| Parent link: | Bulletin of the Tomsk Polytechnic University/ Tomsk Polytechnic University (TPU).— , 2006-2007 Vol. 311, № 5.— 2007.— [P. 102-105] |
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| Sažetak: | Заглавие с титульного листа Электронная версия печатной публикации Aspects of neutral network construction and its learning for increasing accuracy of gas concentration reduction by measuring data of CO2-laser trass gas analyzer have been considered. Accuracy of reducing atmospheric gas (Н2О, СО2 и О3) concentration by neural network method in comparison with traditionally used method of least square is given |
| Jezik: | engleski |
| Izdano: |
2007
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| Serija: | Control, computer engineeringand information science |
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| Online pristup: | http://www.lib.tpu.ru/fulltext/v/Bulletin_TPU/2007/v311eng/i5/22.pdf |
| Format: | Elektronički Poglavlje knjige |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=183097 |
| Opis fizičkog objekta: | 1 файл (321 Кб) |
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| Sažetak: | Заглавие с титульного листа Электронная версия печатной публикации Aspects of neutral network construction and its learning for increasing accuracy of gas concentration reduction by measuring data of CO2-laser trass gas analyzer have been considered. Accuracy of reducing atmospheric gas (Н2О, СО2 и О3) concentration by neural network method in comparison with traditionally used method of least square is given |