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

Guerra Bendezu, Carlos Andres; Romani Franco, Vivian Isabel

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

dc.contributor.advisor	Lopez Gonzales, Javier Linkolk
dc.contributor.author	Guerra Bendezu, Carlos Andres
dc.contributor.author	Romani Franco, Vivian Isabel
dc.date.accessioned	2024-07-14T18:12:09Z
dc.date.available	2024-07-14T18:12:09Z
dc.date.embargoEnd	2026-04-15
dc.date.issued	2024-04-15
dc.description.abstract	In 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.format	application/pdf
dc.identifier.uri	http://repositorio.upeu.edu.pe/handle/20.500.12840/7716
dc.language.iso	spa
dc.publisher	Universidad Peruana Unión
dc.publisher.country	PE
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subject	Air pollution
dc.subject	Hybrid methodology
dc.subject	Artificial Neural Networks
dc.subject	Time series Forecasting
dc.subject.ocde	http://purl.org/pe-repo/ocde/ford#1.01.03
dc.title	Enfoque predictivo para la concentración de contaminante del aire basado en un modelo de red neuronal artificial
dc.type	info:eu-repo/semantics/bachelorThesis
renati.advisor.dni	46071566
renati.advisor.orcid	https://orcid.org/0000-0003-0847-0552
renati.author.dni	08144929
renati.author.dni	09726163
renati.discipline	542039
renati.juror	Abanto Ramirez, Carlos Daniel
renati.level	http://purl.org/pe-repo/renati/nivel#tituloSegundaEspecialidad
renati.type	http://purl.org/pe-repo/renati/type#tesis
thesis.degree.discipline	Segunda Especialidad en Estadística Aplicada para Investigación
thesis.degree.grantor	Universidad Peruana Unión. Unidad de Posgrado de Ingeniería y Arquitectura
thesis.degree.name	Segunda Especialidad Profesional de Ingeniería: Estadística para Investigación