Artificial hydrocarbon networks fuzzy inference system

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dc.contributor.authorPonce Cruz, Pedro
dc.contributor.authorMolina Gutiérrez, Arturo
dc.creatorPONCE CRUZ, PEDRO; 31857es
dc.creatorMOLINA GUTIERREZ, ARTURO; 15309es
dc.date2013
dc.date.accessioned2018-10-18T22:08:24Z
dc.date.available2018-10-18T22:08:24Z
dc.descriptionThis paper presents a novel fuzzy inference model based on artificial hydrocarbon networks, a computational algorithm for modeling problems based on chemical hydrocarbon compounds. In particular, the proposed fuzzy-molecular inference model (FIM-model) uses molecular units of information to partition the output space in the defuzzification step. Moreover, these molecules are linguistic units that can be partially understandable due to the organized structure of the topology and metadata parameters involved in artificial hydrocarbon networks. In addition, a position controller for a direct current (DC) motor was implemented using the proposed FIM-model in type-1 and type-2 fuzzy inference systems. Experimental results demonstrate that the fuzzy-molecular inference model can be applied as an alternative of type-2 Mamdani's fuzzy control systems because the set of molecular units can deal with dynamic uncertainties mostly present in real-world control applications. © 2013 Hiram Ponce et al.
dc.identifier.doi10.1155/2013/531031
dc.identifier.issn1024123X
dc.identifier.urihttp://hdl.handle.net/11285/630575
dc.identifier.volume2013
dc.languageeng
dc.relationhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84885669016&doi=10.1155%2f2013%2f531031&partnerID=40&md5=685628a1eec057c9edebd3f50a11167f
dc.relationInvestigadores
dc.relationEstudiantes
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.sourceMathematical Problems in Engineering
dc.subjectComputational algorithm
dc.subjectControl applications
dc.subjectDynamic uncertainty
dc.subjectFuzzy inference model
dc.subjectFuzzy inference systems
dc.subjectHydrocarbon compounds
dc.subjectOrganized structure
dc.subjectPosition controller
dc.subjectChemical compounds
dc.subjectFuzzy inference
dc.subjectFuzzy systems
dc.subjectMolecular structure
dc.subjectHydrocarbons
dc.subject.classification7 INGENIERÍA Y TECNOLOGÍA
dc.titleArtificial hydrocarbon networks fuzzy inference system
dc.typeArtículo
refterms.dateFOA2018-10-18T22:08:24Z

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