Clustering and uncertainty analysis to improve the machine learning-based predictions of SAFARI-1 control follower assembly axial neutron flux profiles-Reference-Cited by-同舟云学术

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Clustering and uncertainty analysis to improve the machine learning-based predictions of SAFARI-1 control follower assembly axial neutron flux profiles

Published:2024-10 Issue: Volume:206 Page:110630
ISSN:0306-4549
Container-title:Annals of Nuclear Energy
language:en
Short-container-title:Annals of Nuclear Energy

Author:

Moloko Lesego E.^ORCID,Bokov Pavel M.^ORCID,Wu Xu^ORCID,Ivanov Kostadin N.

Publisher

Elsevier BV

Reference44 articles.

1. A review of uncertainty quantification in deep learning: Techniques, applications and challenges;Abdar;Inf. Fusion,2021

2. Survey of state-of-the-art mixed data clustering algorithms;Ahmad;IEEE Access,2019

3. The k-means algorithm: A comprehensive survey and performance evaluation;Ahmed;Electronics,2020

4. Optimization of flux mapping in-core detector locations in AHWR using clustering approach;Anupreethi;Nucl. Eng. Des.,2020

5. Weight uncertainty in neural network;Blundell,2015

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