Prediction of Tropospheric Ozone Concentration by Employing Artificial Neural Networks

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dc.contributor.authorOzdemir, Huseyin
dc.contributor.authorDemir, Goksel
dc.contributor.authorAltay, Gokmen
dc.contributor.authorAlbayrak, Sefika
dc.contributor.authorBayat, Cuma
dc.date.accessioned2024-03-13T10:35:32Z
dc.date.available2024-03-13T10:35:32Z
dc.date.issued2008
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractAir pollution modeling and prediction have great importance in preventing the occurrence of air pollution episodes and provide sufficient time to take the necessary precautions. Recently various algorithms such as artificial neural networks (ANNs) is applied to air quality modeling. The present work aims to predict tropospheric ozone concentration by the ANN with three pollutant parameters and eight meteorological factors in selected areas. We have preferred three-layer perceptron type of ANNs, which consists of input, hidden, and output layers, respectively. To evaluate the performance of the ANN model, selected statistical performance parameters are used. The overall system finds correlation parameter, r between 0.8 and 0.9 for the test data sets. Therefore, results show the successful follow of estimated ozone concentrations by the model with the observed values. Finally, it was seen that the ANN is one of the compromising methods in estimation of environmental complex air pollution problems.en_US
dc.identifier.doi10.1089/ees.2007.0183
dc.identifier.endpage1254en_US
dc.identifier.issn1092-8758
dc.identifier.issn1557-9018
dc.identifier.issue9en_US
dc.identifier.scopus2-s2.0-56249136260en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage1249en_US
dc.identifier.urihttps://doi.org/10.1089/ees.2007.0183
dc.identifier.urihttps://hdl.handle.net/20.500.12662/4473
dc.identifier.volume25en_US
dc.identifier.wosWOS:000261150100003en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMary Ann Liebert, Incen_US
dc.relation.ispartofEnvironmental Engineering Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjecttropospheric ozoneen_US
dc.subjectartificial neural networks (ANN)en_US
dc.subjectIstanbulen_US
dc.subjectpredictionen_US
dc.titlePrediction of Tropospheric Ozone Concentration by Employing Artificial Neural Networksen_US
dc.typeArticleen_US

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