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Estimation of bremsstrahlung photon fluence from aluminum by artificial neural network

dc.contributor.authorAkkurt, İskender
dc.contributor.authorGünoǧlu, Kadir
dc.contributor.authorTekin, Huseyin Ozan
dc.contributor.authorDemirci, Zehra Nur
dc.contributor.authorYeǧin, Gültekin
dc.contributor.buuauthorDemir, Nilgün
dc.contributor.departmentFen Edebiyat Fakültesi
dc.contributor.departmentFizik Bölümü
dc.contributor.orcid0000-0003-2245-8461
dc.contributor.researcheridAAH-3156-2021
dc.contributor.scopusid7006874016
dc.date.accessioned2022-04-25T09:09:45Z
dc.date.available2022-04-25T09:09:45Z
dc.date.issued2012-06
dc.description.abstractBackground: As bremsstrahlung photon beam fluence is important parameter to be known in a photonuclear reaction experiment as the number of produced particle is strongly depends on photon fluence. Materials and Methods: Photon production yield from different thickness of aluminum target has been estimated using artificial neural network (ANN) model. Target thickness and incoming electron energy has been used as input in ANN model and the photon fluence was output. Results: The results were estimated using ANN model for three different thickness and compared with the results obtained by EGS (Electron Gamma Shower) simulation. Conclusion: It can be concluded from this work that the bremsstrahlung photon fluence can be obtained using ANN model.
dc.identifier.citationAkkurt, İ. vd. (2012). "Estimation of bremsstrahlung photon fluence from aluminum by artificial neural network". Iranian Journal of Radiation Research, 10(1), 63-65.
dc.identifier.endpage65
dc.identifier.issn1728-4554
dc.identifier.issue1
dc.identifier.scopus2-s2.0-84864093054
dc.identifier.startpage63
dc.identifier.urihttp://ijrr.com/browse.php?mag_id=37&slc_lang=en&sid=1
dc.identifier.urihttp://hdl.handle.net/11452/26038
dc.identifier.volume10
dc.identifier.wos000314275400009
dc.indexed.wosSCIE
dc.language.isoen
dc.publisherIjrr-Iranian Journal Radiation Res
dc.relation.collaborationYurt içi
dc.relation.journalIranian Journal of Radiation Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectRadiology, nuclear medicine & medical imaging
dc.subjectAnn
dc.subjectEgs
dc.subjectPhoton fluence
dc.subject.emtreeAluminum
dc.subject.emtreeArticle
dc.subject.emtreeArtificial neural network
dc.subject.emtreeBremsstrahlung photon fluence
dc.subject.emtreeElectron
dc.subject.emtreeElectron gamma shower simulation
dc.subject.emtreeMeasurement
dc.subject.emtreePhoton
dc.subject.emtreeRadiation energy
dc.subject.emtreeRadiological parameters
dc.subject.emtreeSimulation
dc.subject.emtreeThickness
dc.subject.scopusCompressive Strength; High Performance Concrete; Concrete Mixtures
dc.subject.wosRadiology, nuclear medicine & medical imaging
dc.titleEstimation of bremsstrahlung photon fluence from aluminum by artificial neural network
dc.typeArticle
dc.wos.quartileQ4
dspace.entity.typePublication
local.contributor.departmentFen Edebiyat Fakültesi/Fizik Bölümü
local.indexed.atScopus
local.indexed.atWOS

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