Hybrid neural network for the adjustment of fuzzy systems when simulating tests of internal combustion engines

dc.contributor.author	Zubkov E.
dc.contributor.author	Galiullin L.
dc.date.accessioned	2018-09-18T20:17:55Z
dc.date.available	2018-09-18T20:17:55Z
dc.date.issued	2011
dc.identifier.issn	1068-798X
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/138447
dc.description.abstract	The use of a hybrid neural network for automatic formulation of fuzzy control rules is considered, in the testing of internal combustion engines. The topology of this network is determined. On the basis of the resulting fuzzy rules, the quality of combustion-engine control is assessed. © 2011 Allerton Press, Inc.
dc.relation.ispartofseries	Russian Engineering Research
dc.title	Hybrid neural network for the adjustment of fuzzy systems when simulating tests of internal combustion engines
dc.type	Article
dc.relation.ispartofseries-issue	5
dc.relation.ispartofseries-volume	31
dc.collection	Публикации сотрудников КФУ
dc.relation.startpage	439
dc.source.id	SCOPUS1068798X-2011-31-5-SID79958090494

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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.