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

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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