Feature extraction for improved disruption prediction analysis at JET

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dc.contributor.authorRattá, G.A.
dc.contributor.authorVega, J.
dc.contributor.authorMurari, A.
dc.contributor.authorJohnson, M.
dc.contributor.authorJET-EFDA Contributors
dc.date.accessioned2025-01-29T13:57:17Z
dc.date.available2025-01-29T13:57:17Z
dc.date.issued2008-10
dc.description.abstractDisruptions are major instabilities and remain one of the main problems in tokomaks. Using Joint European Torus database, a disruption predictor is developed by computational methods including supervised learning techniques. The main objectives of the work are to develop accurate automatic classifiers, to test their performances, and to determine how much in advance of the disruption they can operate with acceptable reliability.es_ES
dc.identifier.citationRattá, G. A., et al. "Feature extraction for improved disruption prediction analysis at JET." Review of scientific instruments 79.10 (2008).es_ES
dc.identifier.issn1089-7623
dc.identifier.urihttps://hdl.handle.net/20.500.14855/4429
dc.language.isoenges_ES
dc.publisherAIP Publishinges_ES
dc.rights.accessRightsembargoed accesses_ES
dc.subjectFeaturees_ES
dc.subjectExtractiones_ES
dc.subjectdisruptiones_ES
dc.subjectnuclear fusiones_ES
dc.subjectdataes_ES
dc.titleFeature extraction for improved disruption prediction analysis at JETes_ES
dc.typejournal articlees_ES

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