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Yazar "Yesilkanat, Cafer Mert" seçeneğine göre listele

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  • Küçük Resim Yok
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    Estimation of radon flux spatial distribution in Rize, Turkey by the artificial neural networks method
    (Pergamon-Elsevier Science Ltd, 2019) Yesilkanat, Cafer Mert; Akbulut Özen, Songül
    In 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.
  • Küçük Resim Yok
    Öğe
    Health risk assessment of soil trace elements using the Sequential Gaussian Simulation approach
    (Springer Heidelberg, 2022) Akbulut Ozen, Songul; Yesilkanat, Cafer Mert; Ozen, Murat; Bassari, Asiye; Taskin, Halim
    In this study, the performance of the Sequential Gaussian Simulation (SGS) approach was studied with the aim of accurately determining local health risk distributions associated with trace elements (V, Cr, Mn, Co, Ni, Cu, Zn, As, and Pb). This study plays a crucial role in determining the distribution of health risk levels, especially from heavy metals. In the SGS approach, health risk levels (non-carcinogenic and carcinogenic) were calculated for pixel sizes of 250 x 250 m(2). Results were compared to the conventional Ordinary Kriging (OK) method. The cross-validation performances of both methods were compared. Non-carcinogenic health risks calculated according to SGS and OK for children were, respectively, rho(c): 0.57 and 0.23, RMSE: 0.45 and 0.57, and MAE: 0.33 and 0.43. In the case of adults, non-carcinogenic SGS and OK results were, respectively, rho(c): 0.53 and 0.24, RMSE: 0.06 and 0.07, and MAE: 0.04 and 0.05 for adults. Carcinogenic health risk estimates obtained by SGS and OK were, respectively, rho(c): 0.72 and 0.31, RMSE: 4.1 x 10(-5) and 5.8 x 10(-5), and MAE: 3.2 x 10(-5) and 4.3 x 10(-5) in the case of children, and in the case of adults the results were, respectively, rho(c): 0.71 and 0.30, RMSE: 5 x 10(-6) and 4.3 x 10(-6), and MAE: 4 x 10(-6) and 5 x 10(-6). These results indicated that SGS offered a more accurate approach in determining health risk distributions.

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