Estimation of bremsstrahlung photon fluence from aluminum by artificial neural network

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dc.contributor.authorAkkurt, I
dc.contributor.authorGunoglu, K
dc.contributor.authorTekin, HO
dc.contributor.authorDemirci, ZN
dc.contributor.authorYegin, G
dc.contributor.authorDemir, N
dc.date.accessioned2025-04-10T10:33:14Z
dc.date.available2025-04-10T10:33:14Z
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. Iran. J. Radiat. Res., 2012; 10(1): 63-65
dc.identifier.issn1728-4554
dc.identifier.urihttp://hdl.handle.net/20.500.14701/39551
dc.language.isoEnglish
dc.titleEstimation of bremsstrahlung photon fluence from aluminum by artificial neural network
dc.typeArticle

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