Mostrar el registro sencillo del ítem

dc.contributor.authorRodríguez-Gracia, Diego
dc.contributor.authorPiedra Fernández, José Antonio 
dc.contributor.authorIribarne Martínez, Luis Fernando 
dc.date.accessioned2017-10-31T07:53:13Z
dc.date.available2017-10-31T07:53:13Z
dc.date.issued2015
dc.identifier.isbn978-1-4799-9957-6
dc.identifier.urihttp://hdl.handle.net/10835/5216
dc.description.abstractThis paper presents an adaptive domotic system in green buildings. In our case, the data of sensor and devices were controlled in CIESOL center. The adaptive domotic system uses a Fuzzy Lattice Reasoning classifier for predicting building energy performance depending on the user condition. Training and testing of classifiers were carried out with temperature condition data acquired for 4 months (February, May, July and November) in the case building called CIESOL. The results show a hihg accuracy rates with a mean absolute error between 0% and 0.21%.es_ES
dc.language.isoeses_ES
dc.publisherIEEE Presses_ES
dc.relationinfo:eu-repo/grantAgreement/ES/MINECO/TIN2013-41576-R/ES/Evolución de sistemas dinámicos en la nube: Un escenario marco hacia las interfaces de usuario inteligentes/ESDNEMIUIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.source4th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2015), July 12-16, Okayama, Japanes_ES
dc.titleAdaptive Domotic System in Green Buildingses_ES
dc.typeinfo:eu-repo/semantics/reportes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doihttp://doi.org/10.1109/IIAI-AAI.2015.281es_ES
dc.relation.projectIDTIN2013-41576-Res_ES


Ficheros en el ítem

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 Internacional