Neural model of synchronous generator with nonlinear magnetizing characteristic

dc.contributor.author	Nocon, Adrian
dc.contributor.author	Paszek, Stefan
dc.contributor.editor	Ulrych, Bohuš
dc.date.accessioned	2017-04-03T08:26:08Z
dc.date.available	2017-04-03T08:26:08Z
dc.date.issued	2007
dc.description.abstract-translated	The paper presents the proposal of using artificial neural networks for simulation investigations of synchronous generators working as autonomous supply sources. The comparative analysis of the neural model and that based on the synchronous generator R-L parameters is performed. A three-stage hybrid algorithm consisting of genetic, Nelder-Mead and gradient algorithms was applied to learning the artificial neural network.	en
dc.format	4 s.	cs
dc.format.mimetype	application/pdf
dc.identifier.citation	AMTEE ’07 : seventh international conference on Advanced Methods in the Theory of Electrical Engineering : September 10-12, 2007 [Pilsen, Czech Republic].	en
dc.identifier.isbn	978-80-7043-564-9
dc.identifier.uri	http://hdl.handle.net/11025/25807
dc.language.iso	en	en
dc.publisher	University of West Bohemia	en
dc.rights	© University of West Bohemia	en
dc.rights.access	openAccess	en
dc.subject	synchronní generátor	cs
dc.subject	neurální model	cs
dc.subject.translated	synchronous generator	en
dc.subject.translated	neural model	en
dc.title	Neural model of synchronous generator with nonlinear magnetizing characteristic	en
dc.type	konferenční příspěvek	cs
dc.type	conferenceObject	en
dc.type.status	Peer-reviewed	en
dc.type.version	publishedVersion	en

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