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

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info:eu-repo/semantics/closedAccess

Date

2019

Author

Yeşilkanat, Cafer Mert
Özen, Songül Akbulut

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Citation

Yeşilkanat, 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.

Abstract

In 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

Source

Applied Radiation and Isotopes

Volume

151

URI

https://doi.org/10.1016/j.apradiso.2019.06.006
https://hdl.handle.net/11494/2129

Collections

  • Matematik ve Fen Bilimleri Eğitimi Bölümü Koleksiyonu - Makaleler [48]
  • PubMed İndeksli Yayınlar Koleksiyonu [149]
  • Scopus İndeksli Yayınlar Koleksiyonu [525]
  • WoS İndeksli Yayınlar Koleksiyonu [685]



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