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 (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137, and Be-7) commonly detected in soil samples agreed to within +/- 19.4% of the expanded uncertainty and 2.61% of average bias.
Keywords:
ANN / radionuclides / PBR / soil / measurement time
Source:
Applied Radiation and Isotopes, 2005, 63, 3, 363-366
TY - JOUR
AU - Dragović, Snežana D.
AU - Onjia, Antonije
PY - 2005
UR - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/853
AB - 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 (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137, and Be-7) commonly detected in soil samples agreed to within +/- 19.4% of the expanded uncertainty and 2.61% of average bias.
PB - Pergamon-Elsevier Science Ltd, Oxford
T2 - Applied Radiation and Isotopes
T1 - Prediction of peak-to-background ratio in gamma-ray spectrometry using simplex optimized artificial neural network
EP - 366
IS - 3
SP - 363
VL - 63
DO - 10.1016/j.apradiso.2005.03.009
ER -
@article{
author = "Dragović, Snežana D. and Onjia, Antonije",
year = "2005",
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 (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137, and Be-7) commonly detected in soil samples agreed to within +/- 19.4% of the expanded uncertainty and 2.61% of average bias.",
publisher = "Pergamon-Elsevier Science Ltd, Oxford",
journal = "Applied Radiation and Isotopes",
title = "Prediction of peak-to-background ratio in gamma-ray spectrometry using simplex optimized artificial neural network",
pages = "366-363",
number = "3",
volume = "63",
doi = "10.1016/j.apradiso.2005.03.009"
}
Dragović, S. D.,& Onjia, A.. (2005). Prediction of peak-to-background ratio in gamma-ray spectrometry using simplex optimized artificial neural network. in Applied Radiation and Isotopes
Pergamon-Elsevier Science Ltd, Oxford., 63(3), 363-366.
https://doi.org/10.1016/j.apradiso.2005.03.009
Dragović SD, Onjia A. Prediction of peak-to-background ratio in gamma-ray spectrometry using simplex optimized artificial neural network. in Applied Radiation and Isotopes. 2005;63(3):363-366.
doi:10.1016/j.apradiso.2005.03.009 .
Dragović, Snežana D., Onjia, Antonije, "Prediction of peak-to-background ratio in gamma-ray spectrometry using simplex optimized artificial neural network" in Applied Radiation and Isotopes, 63, no. 3 (2005):363-366,
https://doi.org/10.1016/j.apradiso.2005.03.009 . .
