A probabilistic model for the identification of confinement regimes and edge localized mode behavior, with implications to scaling laws

Journal Article · Mon Oct 15 00:00:00 EDT 2012 · Review of Scientific Instruments

DOI:https://doi.org/10.1063/1.4733307· OSTI ID:22093857

Verdoolaege, Geert; Van Oost, Guido ^[1]

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1. Department of Applied Physics, Ghent University, 9000 Gent (Belgium)

Pattern recognition is becoming an important tool in fusion data analysis. However, fusion diagnostic measurements are often affected by considerable statistical uncertainties, rendering the extraction of useful patterns a significant challenge. Therefore, we assume a probabilistic model for the data and perform pattern recognition in the space of probability distributions. We show the considerable advantage of our method for identifying confinement regimes and edge localized mode behavior, and we discuss the potential for scaling laws.

• OSTI ID: 22093857
• Journal Information: Review of Scientific Instruments, Vol. 83, Issue 10; Other Information: (c) 2012 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); ISSN 0034-6748
• Country of Publication: United States
• Language: English

Related Subjects

71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
CLASSIFICATION
COMPUTER GRAPHICS
DISTRIBUTION
EDGE LOCALIZED MODES
EXTRACTION
GAUSS FUNCTION
MANAGEMENT
PATTERN RECOGNITION
PROBABILISTIC ESTIMATION
PROBABILITY
SCALING LAWS