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Artificial neural networks approach to the voltage sag classification

dc.contributor.authorOrtiz Fernández, Félix 
dc.contributor.authorOrtiz Fernández, Alfredo 
dc.contributor.authorMañana Canteli, Mario 
dc.contributor.authorRenedo Estébanez, Carlos J. 
dc.contributor.authorDelgado San Román, Fernando 
dc.contributor.authorEguíluz Morán, Luis Ignacio
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2020-11-05T15:27:12Z
dc.date.available2020-11-05T15:27:12Z
dc.date.issued2007-03
dc.identifier.isbn978-84-611-4707-6
dc.identifier.issn2172-038X
dc.identifier.otherDPI2002-04416-C04-01es_ES
dc.identifier.urihttp://hdl.handle.net/10902/19575
dc.description.sponsorshipThe authors would like to thank the support of the Spanish Government under the CICYT research project DPI2002-04416-C04-01.es_ES
dc.format.extent5 p.es_ES
dc.language.isoenges_ES
dc.publisherEuropean Association for the Development of Renewable Energies, Environment and Power Quality (EA4EPQ)es_ES
dc.rights© The European Association for the Development of Renewable Energies, Environment and Power Quality (EA4EPQ)es_ES
dc.sourceRenewable Energy and Power Quality Journal (RE&PQJ), 2007, 1(5), 426-430es_ES
dc.sourceInternational Conference on Renewable Energies and Power Quality (ICREPQ’07), Sevillaes_ES
dc.subject.otherPower qualityes_ES
dc.subject.otherVoltage sagses_ES
dc.subject.otherNeural networkses_ES
dc.subject.otherDigital signal processinges_ES
dc.titleArtificial neural networks approach to the voltage sag classificationes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.24084/repqj05.307
dc.type.versionpublishedVersiones_ES


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