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dc.contributor.authorAcosta, Jesús
dc.contributor.authorNebot Castells, M. Àngela
dc.contributor.authorFuertes Armengol, José Mª
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
dc.date.accessioned2016-04-26T08:08:06Z
dc.date.available2016-04-26T08:08:06Z
dc.date.issued2006-10
dc.identifier.citationAcosta, J., Nebot, M., Fuertes, J.M. "Método multiobjetivo de aprendizaje para razonamiento inductivo difuso". 2006.
dc.identifier.urihttp://hdl.handle.net/2117/86170
dc.description.abstractIt has been recognized in various studies that the variations in the granularity (number of classes per variable) and the membership functions have a significant effect in the behaviour of the fuzzy systems. The FIR methodology is not an exception. The efficiency of the qualitative model identification and fuzzy forecast processes of FIR is very influenced by the fuzzification parameters of the system variables (i.e. number of classes and shape of the membership functions). To resolve this problematic we have been presented in previous works hybrid methodologies called Genetic Fuzzy Systems (GFSs) that try to learn in a joint way or by separated those parameters. These methods have used monoobjetive functions for the evaluation of the chromosomes. In this investigation another method of automatic learning is presented. This new method permits to obtain at the same time the fuzzification parameters of the FIR methodology but using Multiobjective Genetic Algorithms. Its main components are described and the results obtained on an environmental application are presented.
dc.format.extent38 p.
dc.language.isospa
dc.relation.ispartofseriesLSI-06-35-R
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject.otherAlgoritmos genéticos multiobjetivo
dc.subject.otherRazonamiento inductivo difuso
dc.subject.otherSistemas genéticos difusos
dc.subject.otherMachine learning
dc.subject.otherConcentraciones de ozono
dc.subject.otherContaminación del aire
dc.subject.otherModelado medioambiental
dc.subject.otherMultiobjective genetic algorithms
dc.subject.otherFuzzy inductive reasoning
dc.titleMétodo multiobjetivo de aprendizaje para razonamiento inductivo difuso
dc.typeExternal research report
dc.contributor.groupUniversitat Politècnica de Catalunya. SOCO - Soft Computing
dc.contributor.groupUniversitat Politècnica de Catalunya. GRINS - Grup de Recerca en Robòtica Intel·ligent i Sistemes
dc.rights.accessOpen Access
drac.iddocument631992
dc.description.versionPostprint (published version)
upcommons.citation.authorAcosta, J., Nebot, M., Fuertes, J.M.
upcommons.citation.publishedtrue


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