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Neural-Network Modeling of Heat Transfer of Benzene in an Electric Field

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dc.contributor.author Mukhutdinov A.
dc.contributor.author Vakhidova Z.
dc.date.accessioned 2018-09-18T20:02:35Z
dc.date.available 2018-09-18T20:02:35Z
dc.date.issued 2015
dc.identifier.issn 0009-2355
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/136006
dc.description.abstract © 2015, Springer Science+Business Media New York. A neural-network model allowing for extraction of new knowledge from experimental data is developed on the basis of studies using modern computer technology. Prediction of an output parameter (relative change in coefficient of thermal conductivity) with a relative error of 4% on a network previously trained by means of a knowledge base is demonstrated. Some features and laws of the heat transfer of benzene in an electric field are established.
dc.relation.ispartofseries Chemical and Petroleum Engineering
dc.subject artificial neural network
dc.subject dielectric liquid
dc.subject electric field
dc.subject heat transfer
dc.subject modeling
dc.title Neural-Network Modeling of Heat Transfer of Benzene in an Electric Field
dc.type Article
dc.relation.ispartofseries-issue 11-12
dc.relation.ispartofseries-volume 50
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 761
dc.source.id SCOPUS00092355-2015-50-11-12-SID84953348470


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

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