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

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dc.authorid0000-0002-7508-7548en_US
dc.authorid0000-0001-8025-2141en_US
dc.contributor.authorYeşilkanat, Cafer Mert
dc.contributor.authorÖzen, Songül Akbulut
dc.date.accessioned2020-06-29T06:59:30Z
dc.date.available2020-06-29T06:59:30Z
dc.date.issued2019
dc.departmentAÇÜ, Eğitim Fakültesien_US
dc.description.abstractIn this study, average radonflux distribution in the Rize province (Turkey) was estimated by the artificial neuralnetworks (ANN) method. For this purpose, terrestrial gamma dose rate (TGDR), which is defined as an importantproxy in determining radonflux distribution, was used. Input parameters that were used for ANN were thenatural radionuclide (238U,232Th and40K) activity values in soil samples taken from 64 stations in Rize Province,data from ambient gamma dose rates (AGDR) directly affecting the distribution of radonflux and data of geo-graphical coordinates. Randomly chosen 42 stations were used for ANN training and data from 22 stations wereused for testing the ANN model. Performance test results gave a Pearson'srvalue of 0.60 (p < 0.001) and RMSEof 0.296. The area that was used for the model was divided into grids of 100 m by 100 m and a spatial dis-tribution map was composed by using ANN predicted radonflux rates at grid nodes, whereby natural radio-nuclide values and Ordinary Kriging predicted values of external gamma dose rates were used for composing themap
dc.identifier.citationYeşilkanat, C. M., & Özen, S. A. (2019). Estimation of radon flux spatial distribution in Rize, Turkey by the artificial neural networks method. Applied Radiation and Isotopes, 151, 207-216.en_US
dc.identifier.doi10.1016/j.apradiso.2019.06.006
dc.identifier.endpage216en_US
dc.identifier.scopusqualityQ2
dc.identifier.startpage207en_US
dc.identifier.urihttps://doi.org/10.1016/j.apradiso.2019.06.006
dc.identifier.urihttps://hdl.handle.net/11494/2129
dc.identifier.volume151en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorYeşilkanat, Cafer Mert
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofApplied Radiation and Isotopes
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.typeArticle

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