Kazan Federal University Digital Repository

Modeling of absorption process using neural networks

Show simple item record

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

This item appears in the following Collection(s)

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

Show simple item record

Search DSpace


Advanced Search

Browse

My Account

Statistics