Feature extraction for improved disruption prediction analysis at JET

G.A. Rattá, J. Vega, A. Murari, M. Johnson

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Disruptions 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. © 2008 American Institute of Physics.
Original languageEnglish
Article number10F328
Pages (from-to)-
JournalReview of Scientific Instruments
Volume79
Issue number10
DOIs
Publication statusPublished - 2008
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Instrumentation

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