Serkan AKKOYUN, Tuncay BAYRAM, Yücel ÖZGÜVEN

116,117,118,119,120,124Sn ve233,234,235,236,238U İzotopları İçin Dev Dipol Rezonans Enerjilerinin Kestirimi

Dev dipol rezonans (GDR) parametrelerini elde etmek için birçok deneysel ve teorik metot uygulanmaktadır.Bu çalışmada, Sn ve U izotopları için GDR enerjileri, yapay sinir ağları (YSA) metodu ile tahmin edilmiştir. Sonuçlara göre, YSA’nın eğitiminde deneysel verilerden ortalama sapma, %1 seviyesindedir. Sn ve U izotopları için tahmin edilen enerjilerdeki ortalama kare hata, 0,034 MeV’dir.Teorik bir model için ise hata, 0,061 MeV’dir.Bu sonuç, GDR enerjileri üzerinde ANN tahmininin, teorik hesaplamalardaki sonuçlardan daha iyi olduğunu göstermektedir.

Anahtar Kelimeler:

Dev dipol rezonans, E1 geçişi, yapay sinir ağları

Giant Dipole Resonence Energy Predictions For 116,117,118,119,120,124Sn and 233,234,235,236,238U Isotopes

Several experimental and thoretical methods are applied for obtaining giant dipole resonance (GDR) parameters. In this study, GDR energies for Sn and U isotopes have been predicted by using artificial neural network (ANN) method. According to the results, in the training of the ANN, the mean deviations from the experimental values are in the order of 1%. The mean square error for the estimated energies of Sn and U isotopes is 0.034 MeV. Similar error value belonging to a theoretical model calculation is 0.061 MeV. This result indicates that ANN predictions on GDR energy give better results according to the theoretical results.

Keywords:

Giant dipole resonance, E1 transition, artificial neural networks,

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