Determination of neutron fluence-to-dose conversion coefficients by means of artificial neural networks.

Autor: Hernandez-Davila VM; Unidad Académica de Estudios Nucleares, Universidad Autónoma de Zacatecas, C. Ciprés 10, Fracc. La Peñuela, 98068 Zacatecas, Zac. México. Electronic address: vic_mc68010@yahoo.com., Soto-Bernal TG, Vega-Carrillo HR
Jazyk: angličtina
Zdroj: Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine [Appl Radiat Isot] 2014 Jan; Vol. 83 Pt C, pp. 249-51. Date of Electronic Publication: 2013 Apr 19.
DOI: 10.1016/j.apradiso.2013.04.014
Abstrakt: An Artificial Neural Network has been designed to determinate the effective dose, the ambient dose equivalent and the personal dose equivalent fluence-to-dose conversion factors using seven count rates obtained with a Bonner Sphere Spectrometer. The data of 211 neutron spectra and their respective fluence-to-dose conversion coefficients were used to train and to test ANN. The ANN was trained using the trainsec algorithm, the definitive ANN was 7:8:9:10. From the 30 set of data used to test the ANN performance the largest difference was 11% that is close to the difference obtained in neutron dosimetry.
(Copyright © 2013 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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