Please use this identifier to cite or link to this item: http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/790
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dc.contributor6207es_ES
dc.contributor.otherhttps://orcid.org/0000-0002-7081-9084es_ES
dc.contributor.otherhttps://orcid.org/0000-0003-2545-4116-
dc.coverage.spatialGlobales_ES
dc.creatorOrtíz Rodríguez, José Manuel-
dc.creatorReyes Alfaro, Arturo-
dc.creatorReyes Haro, Alfredo-
dc.creatorSolís Sánchez, Luis Octavio-
dc.creatorCastañeda Miranda, Rodrígo-
dc.creatorCervantes Miramontes, José Manuel-
dc.creatorVega Carrillo, Héctor René-
dc.date.accessioned2019-03-15T16:32:11Z-
dc.date.available2019-03-15T16:32:11Z-
dc.date.issued2013-07-
dc.identifierinfo:eu-repo/semantics/publishedVersiones_ES
dc.identifier.issn0094-243Xes_ES
dc.identifier.issn1551-7616es_ES
dc.identifier.urihttp://localhost/xmlui/handle/20.500.11845/790-
dc.identifier.urihttps://doi.org/10.48779/ttgv-3n96es_ES
dc.description.abstractIn 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.es_ES
dc.language.isoenges_ES
dc.publisherAIP Publishinges_ES
dc.relationhttps://aip.scitation.org/doi/abs/10.1063/1.4813469es_ES
dc.relation.urigeneralPublices_ES
dc.rightsAtribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.sourceAIP Conference Proceedings, Vol. 1544, No. 1, julio 2013es_ES
dc.subject.classificationCIENCIAS FISICO MATEMATICAS Y CIENCIAS DE LA TIERRA [1]es_ES
dc.subject.otherArtificial neural networkses_ES
dc.subject.otheroptimization techniqueses_ES
dc.subject.otherneutron spectrometry and dosimetryes_ES
dc.subject.otherunfolding codeses_ES
dc.subject.otherLabVIEWes_ES
dc.subject.otherprogramminges_ES
dc.subject.othertechnological innovationes_ES
dc.titleNSDann2BS, a neutron spectrum unfolding code based on neural networks technology and two bonner sphereses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
Appears in Collections:*Documentos Académicos*-- UA Ciencias Nucleares

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