Title : ( Gamma-ray energy spectrum unfolding of plastic scintillators using artificial neural network )
Authors: Khashayar Heshmati , Nima Ghal-Eh , Reza Izadi Najafabadi , Hector Rene Vega-Carrillo ,
Full TextAbstract
In this study, the unfolding of the plastic scintillator spectrum was undertaken using the artificial neural networks tools of MATLAB. To this purpose, the response matrix of the plastic scintillator was generated for 145 energy groups and in 512 pulse-height channels using the MCNPX2.6 code. The results confirmed that the relative error in the gamma-ray energy unfolding with artificial neural networks is less than 3.8%.
Keywords
, Spectrum unfolding; Gamma, ray; Plastic scintillator; Artificial neural network
@article{paperid:1089857,
author = {Heshmati, Khashayar and Ghal-Eh, Nima and Izadi Najafabadi, Reza and Hector Rene Vega-Carrillo},
title = {Gamma-ray energy spectrum unfolding of plastic scintillators using artificial neural network},
journal = {Applied Radiation and Isotopes},
year = {2022},
volume = {186},
number = {1},
month = {August},
issn = {0969-8043},
pages = {110265--110265},
numpages = {0},
keywords = {Spectrum unfolding; Gamma-ray; Plastic scintillator; Artificial neural network},
}
%0 Journal Article
%T Gamma-ray energy spectrum unfolding of plastic scintillators using artificial neural network
%A Heshmati, Khashayar
%A Ghal-Eh, Nima
%A Izadi Najafabadi, Reza
%A Hector Rene Vega-Carrillo
%J Applied Radiation and Isotopes
%@ 0969-8043
%D 2022
