Automated recognition system for ELM classification in JET

Fusion Engineering and Design

Volumn 84, Issue 2-6, 2009, Pages 712-715

  Duro, N ^a,b   Dormido, R ^a,b   Vega, J ^a,c   Dormido Canto, S ^a,b   Farias, G ^a,b   Sanchez J ^a,b   Vargas, H ^a,b   Murari, A ^a,d  

^a CULHAM SCIENCE CENTRE   (United Kingdom)

^b UNIVERSIDAD NACIONAL DE EDUCACIÓN A DISTANCIA   (Spain)

^c CIEMAT   (Spain)

^d Consorzio RFX Associazione EURATOM ENEA per la Fusione ^*  (Italy)

Author keywords

Clustering; ELMs classification; JET; SVM

Indexed keywords

AUTOMATED RECOGNITION; CLASSIFICATION SYSTEM; CLUSTERING; EDGE LOCALIZED MODES; ELECTRON DENSITIES; ELMS CLASSIFICATION; EMPIRICAL METHOD; ENERGY DROP; K-MEANS CLUSTERING METHOD; NON-LINEAR PHENOMENA; SVM; TEMPORAL SEGMENTS;

COMPUTER VISION; DATABASE SYSTEMS; EDUCATION; JETS; PLASMA DIAGNOSTICS; PLASMA STABILITY; SUPPORT VECTOR MACHINES;

PATTERN RECOGNITION SYSTEMS;

EID: 67349212904     PISSN: 09203796     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fusengdes.2008.12.003     Document Type: Article

References (6)

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2. Saibene G., Horton L.D., Sartori R., Balet B., Clement S., Conway G.D., et al. The influence of isotope mass, edge magnetic shear and input power on high density ELM and H modes in JET. Nuclear Fusion 39 9 (1999) 1133-1156
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6. http://users.jet.efda.org/pages/s1-task-force/index.html