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dc.contributor.authorJove Pérez, Esteban
dc.contributor.authorAláiz Moretón, Héctor
dc.contributor.authorCasteleiro Roca, José L.
dc.contributor.authorCorchado Rodríguez, Emilio Santiago 
dc.contributor.authorCalvo Rolle, José L.
dc.date.accessioned2017-09-06T09:17:04Z
dc.date.available2017-09-06T09:17:04Z
dc.date.issued2014
dc.identifier.citationIntelligent Data Engineering and Automated Learning – IDEAL 2014 Lecture Notes in Computer Science. Volumen 8669, pp. 275-285.
dc.identifier.isbn978-3-319-10839-1 (Print) / 978-3-319-10840-7(Online)
dc.identifier.issn0302-9743 (Print) / 1611-3349 (Online)
dc.identifier.urihttp://hdl.handle.net/10366/135152
dc.description.abstractThe clean energy use has increased during the last years, especially, electricity generation through wind energy. Wind generator blades are usually made by bicomponent mixing machines. With the aim to predict the behavior of this type of manufacturing systems, it has been developed a model that allows to know the performance of a real bicomponent mixing equipment. The novel approach has been obtained by using clustering combined with regression techniques with a dataset obtained during the system operation. Finally, the created model has been tested with very satisfactory results.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherSpringer Science + Business Media
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleModeling of Bicomponent Mixing System Used in the Manufacture of Wind Generator Blades
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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Attribution-NonCommercial-NoDerivs 3.0 Unported
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Unported