Computational Intelligence Techniques for Data Analysis

dc.contributor.author	Bodyanskiy, Yevgeniy
dc.contributor.editor	Jantke, Klaus P.
dc.contributor.editor	Fähnrich, Klaus-Peter
dc.contributor.editor	Wittig, Wolfgang S.
dc.date.accessioned	2019-08-27T08:15:04Z
dc.date.available	2019-08-27T08:15:04Z
dc.date.issued	2005
dc.description.abstract	The paper is a survey of the computational intelligence methods and their application to the data analysis problems. Neural networks, fuzzy sets, neuro-fuzzy systems, and genetic algorithms are considered. The advantages and disadvantages of the soft computing tools as well as specific issues of their application to data processing are analyzed, and the directions for their further improvement are outlined. New clustering algorithms that can operate under substantial uncertainty and cluster overlap are proposed.	en
dc.identifier.isbn	3-88579-401-2
dc.identifier.pissn	1617-5468
dc.identifier.uri	https://dl.gi.de/handle/20.500.12116/24880
dc.language.iso	en
dc.publisher	Gesellschaft für Informatik e. V.
dc.relation.ispartof	Marktplatz Internet: Von e-Learning bis e-Payment, 13. Leipziger Informatik-Tage (LIT 2005)
dc.relation.ispartofseries	Lecture Notes in Informatics (LNI) - Proceedings, Volume P-71
dc.title	Computational Intelligence Techniques for Data Analysis	en
dc.type	Text/Conference Paper
gi.citation.endPage	36
gi.citation.publisherPlace	Bonn
gi.citation.startPage	15
gi.conference.date	21.-23. September 2005
gi.conference.location	Leipzig
gi.conference.sessiontitle	Regular Research Papers

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