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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 ...
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 ...
Artificial neural network model to predict the compressive strength of eco-friendly geopolymer concrete incorporating silica fume and natural zeolite
(Journal of Cleaner Production, 2020)
The growing concern about global climate change and its adverse impacts on societies is putting severe pressure on the construction industry as one of the largest producers of greenhouse gases. Given the environmental ...
Determinants of learning management systems adoption in Nigeria: A hybrid SEM and artificial neural network approach
(Education and Information Technologies, 2020)
Research has shown that technology, when used prudently, has the potential to improve instruction and learning both in and out of the classroom. Only a handful of African tertiary institutions have fully deployed learning ...
Estimation of (n,p) reaction cross sections at 14.5 ∓ 0.5 MeV neutron energy by using artificial neural network
(Applied Radiation and Isotopes, 2021)
The aim of this study is to develop an accurate artificial neural network algorithm for the cross-section of (n,p) reactions at 14.5 ∓0.5 MeV neutron energy which is important to developing materials for fusion reactor ...
