Estimation of radon flux spatial distribution in Rize, Turkey by the artificial neural networks method

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dc.authorid0000-0001-8025-2141en_US
dc.contributor.authorYesilkanat, Cafer Mert
dc.contributor.authorAkbulut Özen, Songül
dc.date.accessioned2021-03-20T20:12:31Z
dc.date.available2021-03-20T20:12:31Z
dc.date.issued2019
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Fizik Bölümüen_US
dc.description.abstractIn this study, average radon flux distribution in the Rize province (Turkey) was estimated by the artificial neural networks (ANN) method. For this purpose, terrestrial gamma dose rate (TGDR), which is defined as an important proxy in determining radon flux distribution, was used. Input parameters that were used for ANN were the natural radionuclide (U-238, Th-232 and K-40) activity values in soil samples taken from 64 stations in Rize Province, data from ambient gamma dose rates (AGDR) directly affecting the distribution of radon flux and data of geographical coordinates. Randomly chosen 42 stations were used for ANN training and data from 22 stations were used for testing the ANN model. Performance test results gave a Pearson's r value of 0.60 (p < 0.001) and RMSE of 0.296. The area that was used for the model was divided into grids of 100 m by 100 m and a spatial distribution map was composed by using ANN predicted radon flux rates at grid nodes, whereby natural radionuclide values and Ordinary Kriging predicted values of external gamma dose rates were used for composing the map.en_US
dc.identifier.doi10.1016/j.apradiso.2019.06.006en_US
dc.identifier.endpage216en_US
dc.identifier.issn0969-8043
dc.identifier.pmid31203051en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage207en_US
dc.identifier.urihttp://doi.org/10.1016/j.apradiso.2019.06.006
dc.identifier.urihttps://hdl.handle.net/20.500.12885/595
dc.identifier.volume151en_US
dc.identifier.wosWOS:000482244900030en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorAkbulut Özen, Songül
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofApplied Radiation And Isotopesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectRadon fluxen_US
dc.subjectTerrestrial gamma dose rateen_US
dc.subjectArtificial neural networken_US
dc.subjectDistribution mappingen_US
dc.subjectRizeen_US
dc.titleEstimation of radon flux spatial distribution in Rize, Turkey by the artificial neural networks methoden_US
dc.typeArticleen_US

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