Publication:
Forecasting PM10 Levels Using ANN and MLR: A Case Study for Sakarya City

Simple item page
dc.authorscopusid57210614739
dc.authorscopusid36238723800
dc.contributor.authorCeylan, C.
dc.contributor.authorBulkan, S.
dc.date.accessioned2020-06-21T13:10:55Z
dc.date.available2020-06-21T13:10:55Z
dc.date.issued2018
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Ceylan] Zeynep, Department of Industrial Engineering, Marmara Üniversitesi, Istanbul, Turkey, Department of Industrial Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Bulkan] Serol, Department of Industrial Engineering, Marmara Üniversitesi, Istanbul, Turkeyen_US
dc.description.abstractIn this study, potential of neural network to estimate daily mean PM10 concentration levels in Sakarya city, Turkey as a case study was examined to achieve improved prediction ability. The level and distribution of air pollutants in a particular region is associated with changes in meteorological conditions affecting air movements and topographic features. Thus, meteorological variables data for a two-year period for Sakarya city which is located in most industrialized and crowded part of Turkey were selected as input. Neural network models and multiple linear regression models have been statistically evaluated. The results of the study showed that ANN models were accurate enough for prediction of PM<inf>10</inf> levels. © 2018, Global NEST. All rights reserved.en_US
dc.identifier.doi10.30955/gnj.002522
dc.identifier.endpage290en_US
dc.identifier.issn1790-7632
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85055025750
dc.identifier.scopusqualityQ3
dc.identifier.startpage281en_US
dc.identifier.urihttps://doi.org/10.30955/gnj.002522
dc.identifier.volume20en_US
dc.identifier.wosWOS:000446340100012
dc.identifier.wosqualityQ4
dc.language.isoenen_US
dc.publisherGlobal NEST 30 Voulgaroktonou str GR114 72 Athens 11472en_US
dc.relation.ispartofGlobal Nest Journalen_US
dc.relation.journalGlobal Nest Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial Neural Networken_US
dc.subjectMulti-Linear Regressionen_US
dc.subjectParticulate Matteren_US
dc.subjectPM10en_US
dc.subjectPredictionen_US
dc.titleForecasting PM10 Levels Using ANN and MLR: A Case Study for Sakarya Cityen_US
dc.typeArticleen_US
dspace.entity.typePublication

Files

Collections

Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu