98 citations · 99 across the 3 of their papers we have counts for
4 papers
One and two proton separation energies from nuclear mass systematics using neural networks
S. Athanassopoulos, E. Mavrommatis, K. A. Gernoth +1
We deal with the systematics of one and two proton separation energies as predicted by our latest global model for the masses of nuclides developed with the use of neural networks.…
Modeling Nuclear Properties with Support Vector Machines
Haochen Li, J. W. Clark, E. Mavrommatis +2
We have made initial studies of the potential of support vector machines (SVM) for providing statistical models of nuclear systematics with demonstrable predictive power. Using SVM…
Nuclear mass systematics using neural networks
S. Athanassopoulos, E. Mavrommatis, K. A. Gernoth +1
New global statistical models of nuclidic (atomic) masses based on multilayered feedforward networks are developed. One goal of such studies is to determine how well the existing d…
Statistical Modeling of Nuclear Systematics
J. W. Clark, E. Mavrommatis, S. Athanassopoulos +2
Statistical modeling of data sets by neural-network techniques is offered as an alternative to traditional semiempirical approaches to global modeling of nuclear properties. New re…