title: Prediction of peak-to-background ratio in gamma-ray spectrometry using simplex optimized artificial neural network.
abstract: An artificial neural network (ANN) model was used for the prediction of peak-to-background ratio (PBR) as a function of measurement time in gamma-ray spectrometry. In order to make the ANN model with good predictive power, the ANN parameters were optimized simultaneously employing a variable-size simplex method. Most of the predicted and the experimental PBR values for eight radionuclides ((226)Ra, (238)U, (235)U, (40)K, (232)Th, (134)Cs, (137)Cs, and (7)Be) commonly detected in soil samples agreed to within +/-19.4% of the expanded uncertainty and 2.61% of average bias.
authors.affiliation: Institute for the Application of Nuclear Energy-INEP, Banatska 31b, 11080 Belgrade, Serbia and Montenegro.
authors.forename: Snezana
authors.initials: S
authors.lastname: Dragović
authors.forename: Antonije
authors.initials: A
authors.lastname: Onjia