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dc.creatorContreras J.
dc.creatorAcuña O.
dc.date.accessioned2020-03-26T16:33:00Z
dc.date.available2020-03-26T16:33:00Z
dc.date.issued2009
dc.identifier.citationAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
dc.identifier.isbn9781424445776
dc.identifier.urihttps://hdl.handle.net/20.500.12585/9125
dc.description.abstractIn this paper we present a new method to generate interpretable fuzzy systems from training data. A fuzzy system is developed for nonlinear systems modeling and for system state forecasting. The antecedent partition uses triangular sets with 0.5 interpolations avoiding the presence of complex overlapping that happens in other methods. Singleton consequents are employed and least square method is used to adjust the consequents. This approach is not a hybrid system and does not employ other techniques, like neural network or genetic algorithm. Two benchmark problems have been used to illustrate our approach: the first one is an input-output NARMAX model, which is one of the most popular models in the neural and fuzzy literature; the second one is the chaotic, nonperiodic and nonconvergence Mackey-Glass series, commonly used to evaluate a time series forecasting scheme. ©2009 IEEE.eng
dc.description.sponsorshipMinist. Commun. Inf. Technol. Azerbaijan
dc.format.mediumRecurso electrónico
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourcehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-70350426514&doi=10.1109%2fNAFIPS.2009.5156422&partnerID=40&md5=acd20cb69276fbda7287db513a2967e9
dc.sourceScopus2-s2.0-70350426514
dc.titleGenerating dynamic fuzzy models for prediction problems
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datacite.rightshttp://purl.org/coar/access_right/c_16ec
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94f
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
dc.source.event2009 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2009
dc.type.driverinfo:eu-repo/semantics/conferenceObject
dc.type.hasversioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doi10.1109/NAFIPS.2009.5156422
dc.subject.keywordsDynamic systems
dc.subject.keywordsFuzzy identification
dc.subject.keywordsInterpretability
dc.subject.keywordsLeast squares method
dc.subject.keywordsBench-mark problems
dc.subject.keywordsDynamic systems
dc.subject.keywordsFuzzy identification
dc.subject.keywordsFuzzy literature
dc.subject.keywordsFuzzy models
dc.subject.keywordsInput-output
dc.subject.keywordsInterpretability
dc.subject.keywordsLeast square methods
dc.subject.keywordsLeast squares method
dc.subject.keywordsNARMAX model
dc.subject.keywordsPrediction problem
dc.subject.keywordsSystem state
dc.subject.keywordsTime series forecasting
dc.subject.keywordsTraining data
dc.subject.keywordsTriangular sets
dc.subject.keywordsComposite structures
dc.subject.keywordsData processing
dc.subject.keywordsDynamic programming
dc.subject.keywordsFuzzy systems
dc.subject.keywordsHybrid systems
dc.subject.keywordsNonlinear systems
dc.subject.keywordsTime series
dc.subject.keywordsFuzzy logic
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.ccAtribución-NoComercial 4.0 Internacional
dc.identifier.instnameUniversidad Tecnológica de Bolívar
dc.identifier.reponameRepositorio UTB
dc.relation.conferenceplaceCincinnati, OH
dc.relation.conferencedate14 June 2009 through 17 June 2009
dc.type.spaConferencia
dc.identifier.orcid35104582500
dc.identifier.orcid35104250500


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Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.