Modelling of SO2 concentrations using artificial neural networks

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dc.contributor.authorDursun S.
dc.contributor.authorGuclu D.
dc.contributor.authorCelebi F.
dc.contributor.authorYilmaz N.
dc.date.accessioned2020-03-26T17:05:26Z
dc.date.available2020-03-26T17:05:26Z
dc.date.issued2006
dc.departmentSelçuk Üniversitesien_US
dc.description6th International Scientific Conference on Modern Management of Mine Producing, Geology and Environmental protection, SGEM 2006 -- 12 June 2006 through 16 June 2006 -- Albena -- 101474en_US
dc.description.abstractModelling of air pollution parameters, according to the meteorological data is a necessary for preventing the repetition of same problems. During recent years, neural network-based models have been shown to be powerful tools in the simulation of variations in air quality and provide better alternative to statistical models because of their computational efficiency and generalization ability. In this study, prediction of future daily SO2 concentrations in Konya (Turkey) using MLP (Multilayer Perceptron) artificial neural networks trained with the back-propagation algorithm, which uses gradient descent optimization for error reduction was employed by taking into account meteorological parameters and SO2 (sulphur dioxide) concentrations obtained for two years period from 2003 to 2004. The appropriate architecture of the neural network models was determined through several steps of trainings and testing of the models. The results illustrated that artificial neural networks offer a valuable method for air pollution management. © 2006. International Scientific Conference SGEM.en_US
dc.identifier.endpage443en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage435en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/20902
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartof6th International Scientific Conference on Modern Management of Mine Producing, Geology and Environmental protection, SGEM 2006en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectAir pollutionen_US
dc.subjectArtificial neural networken_US
dc.subjectKonyaen_US
dc.subjectMeteorological parametersen_US
dc.subjectModelingen_US
dc.subjectSulphur dioxide (SO2)en_US
dc.titleModelling of SO2 concentrations using artificial neural networksen_US
dc.typeConference Objecten_US

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