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Toplam kayıt 11, listelenen: 1-10
Estimations of giant dipole resonance parameters using artificial neural network
(Applied Radiation and Isotopes, 2021)
In this study; Giant Dipole Resonance (GDR) parameters of the spherical nucleus have been estimated by using artificial neural network (ANN) algorithms. The ANN training has been carried out with the Levenberg–Marquardt ...
Estimations for (n,a) reaction cross sections at around 14.5MeV using Levenberg-Marquardt algorithm-based artificial neural network
(Elsevier, 2023)
Prediction of neutron-induced reaction cross-sections at around the 14.5 MeV neutron energy is crucial to calculate nuclear transmutation rates, nuclear heating, and radiation damage from gas formation in fusion reactor ...
Estimations of level density parameters by using artificial neural network for phenomenological level density models
(Applied Radiation and Isotopes, 2021)
The main aim of this study is to develop accurate artificial neural network (ANN) algorithms to estimate level density parameters. An efficient Bayesian-based algorithm is presented for classification algorithms. Unknown ...
Calculation of double differential neutron cross-sections of 56Fe and 90Zr isotopes
(Applied Radiation and Isotopes, 2023)
This study is concerned with the calculations of double differential neutron cross-sections of the structural fusion materials of 56Fe and 90Zr isotopes that are bombarded with protons. Calculations were performed using ...
Investigation of the production routes of Palladium-103 and Iodine-125 radioisotopes
(Radiation Physics and Chemistry, 2023)
The most commonly used radioisotopes are Palladium-103 (103Pd) and Iodine-125 (125I) for interstitial application in brachytherapy. In the present study, different production routes of 103Pd and 125I have been investigated. ...
Investigation of the effects of different composite materials on neutron contamination caused by medical LINAC
(Kerntechnik, 2020)
In a medical linear accelerator, the primary and secondary collimators are generally made of high atomic weight metals. The energy of the x-rays generated by accelerated electrons exceeds the bonding energies of high atomic ...
Mass excess estimations using artificial neural networks
(Applied Radiation and Isotopes, 2022)
Mass excess knowledge is important to investigate the fundamental properties of atomic nuclei. It is a meaningful and important parameter for the determinations of nucleon binding energy, nuclear reaction Q value, energy ...
Neural network predictions of (α, n) reaction cross sections at 18.5±3 MeV using the Levenberg-Marquardt algorithm
(Elsevier, 2024)
In recent developments, artificial neural networks (ANNs) have demonstrated their capability to predict reaction cross-sections based on experimental data. Specifically, for predicting (a,n) reaction cross-sections, we ...
A study on the estimations of (n, t) reaction cross-sections at 14.5 MeV by using artificial neural network
(Modern Physics Letters A, 2021)
In this paper, calculations of the (n,t) reaction cross-sections at 14.5 MeV have been presented by utilizing artificial neural network algorithms (ANNs). The systematics are based on the account for the non-equilibrium ...
Calculations of GDR parameters for deformed nuclei using LogitBoost classifier and artificial neural network
(Modern Physics Letters A, 2022)
Photo-nuclear interactions are important for investigating fundamental nuclear physics phenomena. The photo-absorption cross-section energy curve displays a wide resonance called giant dipole resonance (GDR) until 30 MeV. ...