Título
NSDann2BS, a neutron spectrum unfolding code based on neural networks technology and two bonner spheres
Autor
HECTOR RENE VEGA CARRILLO
Nivel de Acceso
Acceso Abierto
Materias
Resumen o descripción
In this work a neutron spectrum unfolding code, based on artificial intelligence technology is presented. The
code called “Neutron Spectrometry and Dosimetry with Artificial Neural Networks and two Bonner spheres”,
(NSDann2BS), was designed in a graphical user interface under the LabVIEW programming environment. The main features of this code are to use an embedded artificial neural network architecture optimized with the “Robust design of artificial neural networks methodology” and to use two Bonner spheres as the only piece of information. In order to build the code here presented, once the net topology was optimized and properly trained, knowledge stored at synaptic weights was extracted and using a graphical framework build on the LabVIEW programming environment, the NSDann2BS code was designed. This code is friendly, intuitive and easy to use for the end user. The code is freely available upon request to authors. To demonstrate the use of the neural net embedded in the NSDann2BS code, the rate counts of 252Cf, 241AmBe and 239PuBe neutron sources measured with a Bonner spheres system.
Producción Científica de la Universidad Autónoma de Zacatecas UAZ
Fecha de publicación
julio de 2013
Tipo de publicación
Artículo
Recurso de información
Formato
application/pdf
Idioma
Inglés
Audiencia
Público en general
Repositorio Orígen
Repositorio Institucional Caxcán
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