Investigating the Physics of Tokamak Global Stability with Interpretable Machine Learning Tools

The inadequacies of basic physics models for disruption prediction have induced the community to increasingly rely on data mining tools. In the last decade, it has been shown how machine learning predictors can achieve a much better performance than those obtained with manually identified thresholds...

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Auteurs principaux:	Andrea Murari, Emmanuele Peluso, Michele Lungaroni, Riccardo Rossi, Michela Gelfusa, JET Contributors
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2020-09-01
Collection:	Applied Sciences
Sujets:	disruptions prediction support vector machines classification and regression trees (CART) ensemble of classifiers symbolic regression
Accès en ligne:	https://www.mdpi.com/2076-3417/10/19/6683
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