Neural networks for predicting neutron ambiente dose equivalent measured by means of bonner spheres
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2004
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IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD
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A Neural Network structure has been applied for
predicting neutron Ambient Dose Equivalent measured by means
of a Bonner Sphere Spectrometer (BSS) set. The present work
used the SNNS (“Stuttgart Neural Network Simulator”) as the
interface for designing, training and validation of a MultiLayer
Perceptron network. The back-propagation algorithm was
applied . The Bonner Sphere set chosen has been calibrated at the
National Physical Laboratory, United Kingdom, and uses gold
activation foils as thermal neutron detectors. The neutron energy
covered by the response functions goes from 0.0001 eV to 10 MeV.
A set of 27 continuous neutron spectra was used for training and
validating the neural network. Excellent results were obtained,
indicating that the Neural Network can be considered an
interesting alternative for estimating neutron Ambient Dose
Equivalent measured by means of Bonner Spheres.
Como referenciar
BRAGA, C.C.; DIAS, M.S. Neural networks for predicting neutron ambiente dose equivalent measured by means of bonner spheres. In: IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD, Oct. 16-22, 2004, Roma, Italy. Proceedings... DOI: 10.1109/NSSMIC.2004.1462542. Disponível em: http://repositorio.ipen.br/handle/123456789/17502. Acesso em: 20 Mar 2026.
Esta referência é gerada automaticamente de acordo com as normas do estilo IPEN/SP (ABNT NBR 6023) e recomenda-se uma verificação final e ajustes caso necessário.