English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/3515
COMPARTIR / IMPACTO:
Estadísticas
logo share SHARE   Add this article to your Mendeley library MendeleyBASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
Campo DC Valor Lengua/Idioma
dc.contributor.authorMoreno Velo, Francisco José-
dc.contributor.authorBaturone, I.-
dc.contributor.authorSánchez-Solano, Santiago-
dc.contributor.authorBarriga, Angel-
dc.date.accessioned2008-04-10T11:14:12Z-
dc.date.available2008-04-10T11:14:12Z-
dc.date.issued2001-12-
dc.identifier.citationEuropean Symposium on Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems (EUNITE-2001), pp. 241-246, Tenerife, Dec. 2001.en_US
dc.identifier.urihttp://hdl.handle.net/10261/3515-
dc.description.abstractThis paper presents Xfsl, a tool for the automatic tuning of fuzzy systems using supervised learning algorithms. The tool provides a wide set of learning algorithms, which can be used to tune complex systems. An important issue is that Xfsl is integrated into the fuzzy system development environment Xfuzzy 3.0, and hence, it can be easily employed within the design flow of a fuzzy system.en_US
dc.description.sponsorshipThis work has been partially supported by the Spanish CICYT Project TIC98-0869 and the FEDER Project 1FD97-0956-C3-02.en_US
dc.format.extent301775 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoengen_US
dc.rightsopenAccessen_US
dc.subjectAutomatic Tuningen_US
dc.subjectSupervised Learningen_US
dc.subjectCAD Toolsen_US
dc.subjectFuzzy Systemsen_US
dc.titleXFSL: A tool for supervised learning of fuzzy systemsen_US
dc.typeComunicación de congresoen_US
dc.description.peerreviewedPeer revieweden_US
Aparece en las colecciones: (IMSE-CNM) Comunicaciones congresos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
XSFL.pdf294,7 kBAdobe PDFVista previa
Visualizar/Abrir
Show simple item record
 


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.