Determination and mapping the spatial distribution of radioactivity of natural spring water in the Eastern Black Sea Region by using artificial neural network method

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dc.authorid0000-0002-7508-7548en_US
dc.authorid0000-0001-7919-7552en_US
dc.contributor.authorYeşilkanat, Cafer Mert
dc.contributor.authorKobya, Yaşar
dc.date.accessioned2021-09-24T08:24:02Z
dc.date.available2021-09-24T08:24:02Z
dc.date.issued2015
dc.departmentAÇÜ, Eğitim Fakültesi, Matematik ve Fen Bilimleri Eğitimi Bölümüen_US
dc.description.abstractIn this study, radiological distribution of gross alpha, gross beta, Ra-226, Th-232, K-40, and Cs-137 for a total of 40 natural spring water samples obtained from seven cities of the Eastern Black Sea Region was determined by artificial neural network (ANN) method. In the ANN method employed, the backpropagation algorithm, which estimates the backpropagation of the errors and results, was used. In the structure of ANN, five input parameters (latitude, longitude, altitude, major soil groups, and rainfall) were used for natural radionuclides and four input parameters (latitude, longitude, altitude, and rainfall) were used for artificial radionuclides, respectively. In addition, 75 % of the total data were used as the data of training and 25 % of them were used as test data in order to reveal the structure of each radionuclide. It has been seen that the results obtained explain the radiographic structure of the region very well. Spatial interpolation maps covering the whole region were created for each radionuclide including spots not measured by using these results. It has been determined that artificial neural network method can be used for mapping the spatial distribution of radioactivity with this study, which is conducted for the first time for the Black Sea Region.
dc.identifier.citationYeşilkanat, C. M., & Kobya, Y. (2015). Determination and mapping the spatial distribution of radioactivity of natural spring water in the Eastern Black Sea Region by using artificial neural network method. Environmental monitoring and assessment, 187(9), 1-13.en_US
dc.identifier.doi10.1007/s10661-015-4811-0
dc.identifier.endpage13en_US
dc.identifier.issue9en_US
dc.identifier.scopusqualityQ2
dc.identifier.startpage1en_US
dc.identifier.urihttps://hdl.handle.net/11494/3464
dc.identifier.volume187en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorYeşilkanat, Cafer Mert
dc.institutionauthorKobya, Yaşar
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofEnvironmental Monitoring and Assessment
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEnvironmental radioactivityen_US
dc.subjectArtificial neural networken_US
dc.subjectInterpolated mapsen_US
dc.subjectEastern Black Sea Regionen_US
dc.subjectTurkeyen_US
dc.titleDetermination and mapping the spatial distribution of radioactivity of natural spring water in the Eastern Black Sea Region by using artificial neural network methoden_US
dc.typeArticle

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