Enfoque predictivo para la concentración de contaminante del aire basado en un modelo de red neuronal artificial

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dc.contributor.advisorLópez Gonzales, Javier Linkolk
dc.contributor.authorGuerra Bendezu, Carlos Andres
dc.contributor.authorRomani Franco, Vivian Isabel
dc.date.accessioned2024-07-14T18:12:09Z
dc.date.available2024-07-14T18:12:09Z
dc.date.embargoEnd2026-04-15
dc.date.issued2024-04-15
dc.description.abstractIn this study, we propose a new hybrid method based on artificial neural networks to forecast daily extreme events of PM2.5 pollution concentration. The hybrid method combines self-organizing maps to identify temporal patterns of excessive daily pollution found at different monitoring stations, with a set of multilayer perceptron to forecast extreme values of PM2.5 for each cluster. The proposed model was applied to analyze five-year pollution data obtained from nine weather stations in the metropolitan area of Santiago, Chile. Simulation results show that the hybrid method improves the performance metrics when forecasting daily extreme values of PM2.5.
dc.formatapplication/pdf
dc.identifier.urihttps://hdl.handle.net/20.500.12840/7716
dc.language.isospa
dc.publisherUniversidad Peruana Unión
dc.publisher.countryPE
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectAir pollution
dc.subjectHybrid methodology
dc.subjectArtificial Neural Networks
dc.subjectTime series Forecasting
dc.subject.ocdehttp://purl.org/pe-repo/ocde/ford#1.01.03
dc.titleEnfoque predictivo para la concentración de contaminante del aire basado en un modelo de red neuronal artificial
dc.typeinfo:eu-repo/semantics/bachelorThesis
renati.advisor.dni46071566
renati.advisor.orcidhttps://orcid.org/0000-0003-0847-0552
renati.author.dni08144929
renati.author.dni09726163
renati.discipline542039
renati.jurorAbanto Ramírez, Carlos Daniel
renati.levelhttps://purl.org/pe-repo/renati/level#tituloSegundaEspecialidad
renati.typehttp://purl.org/pe-repo/renati/type#tesis
thesis.degree.disciplineSegunda Especialidad en Estadística Aplicada para Investigación
thesis.degree.grantorUniversidad Peruana Unión. Unidad de Posgrado de Ingeniería y Arquitectura
thesis.degree.nameSegunda Especialidad Profesional de Ingeniería: Estadística para Investigación

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