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

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