Please use this identifier to cite or link to this item: http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/790
Title: NSDann2BS, a neutron spectrum unfolding code based on neural networks technology and two bonner spheres
Authors: Ortíz Rodríguez, José Manuel
Reyes Alfaro, Arturo
Reyes Haro, Alfredo
Solís Sánchez, Luis Octavio
Castañeda Miranda, Rodrígo
Cervantes Miramontes, José Manuel
Vega Carrillo, Héctor René
Issue Date: Jul-2013
Publisher: AIP Publishing
Abstract: 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.
URI: http://localhost/xmlui/handle/20.500.11845/790
https://doi.org/10.48779/ttgv-3n96
ISSN: 0094-243X
1551-7616
Other Identifiers: info:eu-repo/semantics/publishedVersion
Appears in Collections:*Documentos Académicos*-- UA Ciencias Nucleares

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