Investigation of Machine Learning Techniques for Disruption Prediction Using JET Data
Disruption prediction and mitigation is of key importance in the development of sustainable tokamak reactors. Machine learning has become a key tool in this endeavour. In this paper, multiple machine learning models are tested and compared. A focus has been placed on the analysis of a transition to...
Main Authors: | Joost Croonen, Jorge Amaya, Giovanni Lapenta |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-02-01
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Series: | Plasma |
Subjects: | |
Online Access: | https://www.mdpi.com/2571-6182/6/1/8 |
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