Improvement studies on neutron-gamma separation in HPGe detectors by using neural networks

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dc.contributor.authorAkkoyun, Serkan
dc.contributor.authorBayram, Tuncay
dc.contributor.authorKara, Seyit Okan
dc.date.accessioned2014-08-27T08:44:33Z
dc.date.available2014-08-27T08:44:33Z
dc.date.issued2013
dc.description.abstractThe neutrons emitted in heavy-ion fusion-evaporation (HIFE) reactions together with the gamma-rays cause unwanted backgrounds in gamma-ray spectra. Especially in the nuclear reactions where relativistic ion beams (RIBs) are used, these neutrons are serious problem. They have to be rejected in order to obtain clearer gamma-ray peaks. In this study, the radiation energy and three criteria which are previously determined for separation of neutron and gamma-rays in the HPGe detectors have been used in artificial neural network (ANN) for improving of the decomposition power. According to the preliminary results, by the help of ANN method, the ratio of neutron rejection has been improved by a factor of 1.27 and the ratio of the lost in gamma-rays has been decreased by a factor of 0.5.
dc.identifier.citationAkkoyun, S., Bayram, T., Kara, S. O. "Improvement studies on neutron-gamma separation in HPGe detectors by using neural networks". Cumhuriyet Science Journal, 34 (2013) 42-51.
dc.identifier.issn1300-1949
dc.identifier.urihttp://dergi.cumhuriyet.edu.tr/cumuscij/article/view/1008001947/1008001715
dc.identifier.urihttps://hdl.handle.net/11486/476
dc.language.isoen
dc.publisherCumhuriyet Science Journal
dc.relation.publicationcategoryMakale - Kategorisiz
dc.subjectHPGe detectors
dc.subjectGamma - raytracking
dc.subjectArtificial neural network
dc.subjectGeant4
dc.subjectNeutron-gamma separation
dc.titleImprovement studies on neutron-gamma separation in HPGe detectors by using neural networks
dc.typeArticle

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