Modeling of absorption process using neural networks

dc.contributor.author	Kharitonova O.
dc.contributor.author	Bronskaya V.
dc.contributor.author	Ignashina T.
dc.contributor.author	Al-Muntaser A.
dc.contributor.author	Khairullina L.
dc.date.accessioned	2020-01-15T21:51:42Z
dc.date.available	2020-01-15T21:51:42Z
dc.date.issued	2019
dc.identifier.issn	1755-1307
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/156314
dc.description.abstract	© 2019 IOP Publishing Ltd. All rights reserved. An artificial neural multi-layer network has been developed for predicting the mass transfer coefficients in the liquid and gas phases for the gas absorption (CO2) from the air using an absorbent - water. For the development of neural network the unobservable parameters of the packed absorber were calculated. The obtained results can be used to model an extensive class of chemical engineering processes with the possibility of formalizing the calculation procedures.
dc.relation.ispartofseries	IOP Conference Series: Earth and Environmental Science
dc.title	Modeling of absorption process using neural networks
dc.type	Conference Paper
dc.relation.ispartofseries-issue	3
dc.relation.ispartofseries-volume	315
dc.collection	Публикации сотрудников КФУ
dc.source.id	SCOPUS17551307-2019-315-3-SID85072834805

Files in this item

Size: 47.61Kb

Format: PDF

Публикации сотрудников КФУ Scopus [24551]
Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.