1 citations · 1 across the 2 of their papers we have counts for
2 papers
eess.SY2025
Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need?
Xu Wu, Lesego E. Moloko, Pavel M. Bokov +3
Machine learning (ML) has been leveraged to tackle a diverse range of tasks in almost all branches of nuclear engineering. Many of the successes in ML applications can be attribute…
cs.LG2023★ 1 cited
Clustering and Uncertainty Analysis to Improve the Machine Learning-based Predictions of SAFARI-1 Control Follower Assembly Axial Neutron Flux Profiles
Lesego Moloko, Pavel Bokov, Xu Wu +1
The goal of this work is to develop accurate Machine Learning (ML) models for predicting the assembly axial neutron flux profiles in the SAFARI-1 research reactor, trained by measu…