Neural Network Estimation for Attenuation Coefficients for Gamma-Ray Angular Distribution

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dc.contributor.authorAkkoyun, Serkan
dc.contributor.authorYildiz, Nihat
dc.contributor.authorKaya, Huseyin
dc.date.accessioned2024-10-26T18:02:41Z
dc.date.available2024-10-26T18:02:41Z
dc.date.issued2019
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description.abstractSpins of nuclear states (J) and multipolarities of gamma rays are usually investigated by the angular distribution of gamma rays emitted from aligned states formed by nuclear reactions. In the case of partial alignment, attenuation coefficients are used in angular distribution function. These coefficients are tabulated in literature for different J values. However, these coefficients involve r-fold tensor products. Furthermore, as the calculation of these coefficients implicitly involves highly complicated integral quantities, they are very difficult to handle explicitly for larger values. In this respect, universal nonlinear function approximator layered feedforward neural network (LFNN) can be applied to construct consistent empirical physical formulas (EPFs) for physical phenomena. In this paper, we consistently estimated the attenuation coefficients by constructing suitable LFNNs. The LFNN-EPFs fitted the literature coefficient data very well. Moreover, magnificent LFNN test set predictionson unseen data confirmed the consistent LFNN-EPFs for the determination of coefficients.
dc.identifier.doi10.1134/S1547477119040034
dc.identifier.endpage401
dc.identifier.issn1547-4771
dc.identifier.issn1531-8567
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85069453555
dc.identifier.scopusqualityQ3
dc.identifier.startpage397
dc.identifier.urihttps://doi.org/10.1134/S1547477119040034
dc.identifier.urihttps://hdl.handle.net/20.500.12418/28275
dc.identifier.volume16
dc.identifier.wosWOS:000476516400009
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPleiades Publishing Inc
dc.relation.ispartofPhysics of Particles and Nuclei Letters
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectGamma-rays angular distribution
dc.subjectattenuation coefficient
dc.subjectlayered feed-forward neural network
dc.titleNeural Network Estimation for Attenuation Coefficients for Gamma-Ray Angular Distribution
dc.typeArticle

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