Please use this identifier to cite or link to this item: http://earchive.tpu.ru/handle/11683/2504
Title: Using neural nets for reducing gas concentrations by the data of trass gas analyzer at CO2-laser
Authors: Kataev, M. Yu.
Sukhanov, A. Ya.
Keywords: neural nets; concentrations; gas; trass gas analyzers; lasers; method of least square
Issue Date: 2007
Publisher: Томский политехнический университет
Citation: Kataev M. Yu. Using neural nets for reducing gas concentrations by the data of trass gas analyzer at CO2-laser / M. Yu. Kataev, A. Ya. Sukhanov // Bulletin of the Tomsk Polytechnic University. — 2007. — Vol. 311, № 5. — [P. 102-105].
Abstract: 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
URI: http://earchive.tpu.ru/handle/11683/2504
Appears in Collections:Известия Томского политехнического университета. Инжиниринг георесурсов

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