An Extended Version ofGustafson-Kessel Clustering Algorithm for Evolving Data Stream Clustering Evolving Intelligent Systems: Methodology and Applications

dc.contributor.author	Filev, D.
dc.contributor.author	Georgieva, Olga
dc.date.accessioned	2010-05-12T14:12:01Z
dc.date.available	2010-05-12T14:12:01Z
dc.date.issued	2010
dc.identifier.citation	D. Filev, O. Georgieva, 2010, An Extended Version of Gustafson-Kessel Clustering Algorithm for Evolving Data Stream Clustering, Evolving Intelligent Systems: Methodology and Applications, (Angelov, Plamen / Filev, Dimitar P. / Kasabov, Nik (eds.)), IEEE Press Series on Computational Intelligence, pp.293-315 (ISBN-10: 0-470-28719-5, ISBN-13: 978-0-470-28719-4- John Wiley & Sons).	bg_BG
dc.identifier.isbn	0-470-28719-5
dc.identifier.uri	http://hdl.handle.net/10506/334
dc.description.abstract	The chapter deals with a recursive clustering algorithm that enables a real time partitioning of data streams. Proposed algorithm incorporates the advantages of the Gustafson-Kessel clustering algorithm of identifying clusters with different shape and orientation while expanding its area of application to the challenging problem of real time data clustering. The algorithm is applicable to a wide range of practical evolving system type applications as diagnostics and prognostics, system identification, real time classification, and process quality monitoring and control.	bg_BG
dc.language.iso	en	bg_BG
dc.publisher	IEEE Press Series on Computational Intelligence	bg_BG
dc.subject	Gustafson-Kessel Clustering Algorithm	bg_BG
dc.subject	Data Stream Clustering	bg_BG
dc.subject	Intelligent Systems	bg_BG
dc.title	An Extended Version ofGustafson-Kessel Clustering Algorithm for Evolving Data Stream Clustering Evolving Intelligent Systems: Methodology and Applications	bg_BG
dc.type	Article	bg_BG