AN ARTIFICIAL NEURAL NETWORK-BASED MODEL FOR SHORT-TERM PREDICTIONS OF DAILY MEAN PM10 CONCENTRATIONS

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dc.contributor.authorDemir, G.
dc.contributor.authorOzdemir, H.
dc.contributor.authorOzcan, H. K.
dc.contributor.authorUcan, O. N.
dc.contributor.authorBayat, C.
dc.date.accessioned2024-03-13T10:33:39Z
dc.date.available2024-03-13T10:33:39Z
dc.date.issued2010
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractPrediction of particulate matter (PM) in the air is an important issue in control and reduction of pollutants in the air. One of the most useful methods to forecast atmospheric pollution is artificial neural network (ANN) because of its high ability to forecast the atmospheric events. In this study ANN technique has been used to predict the PM10 concentration in Istanbul. Meteorological data and PM10 data, which had been collected from Sariyer-Bahcekoy for the one year data, were used. The data were separated into two groups for training and testing the model. The odd days were used for training and the remaining was used for the testing. The transfer function was sigmoid function. In the model, different hidden neuron numbers were altered for proposed ANN structure. We have altered number of neurons for hidden layer between 2 to 10. The prediction of PM10 of the model during the years 2004-2005 follows the actual values with success, with the best calculated correlation coefficient 0.60.en_US
dc.identifier.endpage1171en_US
dc.identifier.issn1311-5065
dc.identifier.issue3en_US
dc.identifier.startpage1163en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12662/4082
dc.identifier.volume11en_US
dc.identifier.wosWOS:000282925000043en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherScibulcom Ltden_US
dc.relation.ispartofJournal Of Environmental Protection And Ecologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPM10en_US
dc.subjectartificial neural networksen_US
dc.subjectpredictionen_US
dc.titleAN ARTIFICIAL NEURAL NETWORK-BASED MODEL FOR SHORT-TERM PREDICTIONS OF DAILY MEAN PM10 CONCENTRATIONSen_US
dc.typeArticleen_US

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