C.M. Yeşilkanat

High-accuracy prediction of Kβ/Kα intensity ratios via explainable stacked-ensemble learning : A web-based computational tool

The Kβ/Kα intensity ratios are critical parameters that quantitatively characterize atomic shell transition dynamics and radiative branching probabilities. In this study, we systematically evaluated the capability of machine learning (ML) algorithms to predict these ratios, as we...