title: Analysis of (7)Be behaviour in the air by using a multilayer perceptron neural network.
abstract: A multilayer perceptron artificial neural network (ANN) model for the prediction of the (7)Be behaviour in the air as the function of meteorological parameters was developed. The model was optimized and tested using (7)Be activity concentrations obtained by standard gamma-ray spectrometric analysis of air samples collected in Belgrade (Serbia) during 2009-2011 and meteorological data for the same period. Good correlation (r = 0.91) between experimental values of (7)Be activity concentrations and those predicted by ANN was obtained. The good performance of the model in prediction of (7)Be activity concentrations could provide basis for construction of models which would forecast behaviour of other airborne radionuclides.
authors.affiliation: Military Technical Institute, Belgrade, Serbia. Electronic address: sale1509@yahoo.com.
authors.forename: A
authors.initials: A
authors.lastname: Samolov
authors.affiliation: Vinča Institute of Nuclear Sciences, Belgrade, Serbia.
authors.forename: S
authors.initials: S
authors.lastname: Dragović
authors.affiliation: Faculty of Physical Chemistry, University of Belgrade, Serbia.
authors.forename: M
authors.initials: M
authors.lastname: Daković
authors.affiliation: Faculty of Physical Chemistry, University of Belgrade, Serbia.
authors.forename: G
authors.initials: G
authors.lastname: Bačić
mesh_terms: D000396:Air Pollutants, Radioactive / Q000032:analysis*; D001608:Beryllium / Q000032:analysis*; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D011834:Radiation Monitoring; D011868:Radioisotopes / Q000032:analysis*; D055771:Serbia; D013051:Spectrometry, Gamma
chemical_list: D000396:Air Pollutants, Radioactive; D011868:Radioisotopes; D001608:Beryllium
keywords: (7)Be; Air; Gamma-ray spectrometry; Neural network