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dc.contributorPonce Cruz, Pedro.
dc.contributorMolina Gutiérrez, Arturo.
dc.contributorPedro Ponce Cruz
dc.contributorArturo Molina Gutiérrez
dc.contributor.authorPonce Espinosa, Hiram Eredín.
dc.creatorPONCE ESPINOSA, HIRAM EREDIN; 376768es_MX
dc.date.accessioned2018-05-07T19:03:58Z
dc.date.available2018-05-07T19:03:58Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/11285/628900
dc.description.abstractIn this work, a new supervised learning method called artificial organic networks is proposed for modeling problems, i.e. fitting, analyzing, inference and classification. In fact, this technique is inspired on chemical organic compounds due to their characteristics of stability, encapsulation, inheritance, organization, and robustness. Additionally, this work presentsartificial hydrocarbon networks, a supervised learning algorithm inspired on chemical hydrocarbon compounds and proposed under artificial organic networks technique.
dc.format.mediumTextoes_MX
dc.language.isoeng
dc.publisherInstituto Tecnológico y de Estudios Superiores de Monterrey
dc.relationInvestigadores
dc.relationEstudiantes
dc.relation.isFormatOfversión publicadaes_MX
dc.relation.isreferencedbyREPOSITORIO NACIONAL CONACYT
dc.rightsopenAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0*
dc.subjectComputer algorithms
dc.subjectOrganic compounds
dc.subjectMachine learning
dc.subjectAlgoritmos computacionales
dc.subject.classificationINGENIERÍA Y TECNOLOGÍA; CIENCIAS TECNOLÓGICAS; TECNOLOGÍA DE LOS ORDENADORES; LENGUAJES ALGORÍTMICOSes_MX
dc.subject.lcshTecnología / Technology
dc.subject.lcshTheory and practice of education--Higher education—Preparation of theseses_MX
dc.titleA new supervised learning algorithm inspired on chemical organic compounds
dc.typeTesis Doctorado / doctoral Thesis
thesis.degree.levelDoctorado en Ciencias Computacionales
thesis.degree.disciplineEscuela de Diseño, Ingeniería y Arquitectura
thesis.degree.programCampus Ciudad de México
dc.audience.educationlevelInvestigadores/Researchers
refterms.dateFOA2018-05-07T19:03:58Z
dc.identificator7
dc.identificator33
dc.identificator3304
dc.identificator120302


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