Selecting differential and integral experiments via machine learning to reduce 239 pu nuclear data uncertainties from 1-600 kev [Poster]
he project PARADIGM (PARallel Approach of Differential and InteGral Measurements) answers this question by selecting via machine learning (ML) an optimal combination of differential and integral experiments to reduce 239 Pu nuclear data uncertainties from 1-600 keV by 50%..