Abstract
The present work continues advanced spatial data analysis of surface contamination by radionuclides after severe nuclear accident on Chernobyl NPP. Feedforward neural networks are used for the Cs137 and Sr90 radionuclides prediction mapping and spatial estimations. Neural networks are used to model complex trends over the entire region. Residuals are analyzed with the help of geostatistical approach within the framework of NNRK (neural network residual kriging) model. Another set of data is used to validate obtained results.
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