eXplainable artificial intelligence applied to algorithms for disruption prediction in tokamak devices

Introduction: This work explores the use of eXplainable artificial intelligence (XAI) to analyze a convolutional neural network (CNN) trained for disruption prediction in tokamak devices and fed with inputs composed of different physical quantities.Methods: This work focuses on a reduced dataset con...

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Bibliographic Details

Published in:	Frontiers in Physics
Main Authors:	L. Bonalumi, E. Aymerich, E. Alessi, B. Cannas, A. Fanni, E. Lazzaro, S. Nowak, F. Pisano, G. Sias, C. Sozzi
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2024-05-01
Subjects:	nuclear fusion disruptions tokamak JET CNN XAI
Online Access:	https://www.frontiersin.org/articles/10.3389/fphy.2024.1359656/full