title: A probabilistic model for the identification of confinement regimes and edge localized mode behavior, with implications to scaling laws.
abstract: 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.
authors.affiliation: Department of Applied Physics, Ghent University, Belgium. geert.verdoolaege@ugent.be
authors.forename: Geert
authors.initials: G
authors.lastname: Verdoolaege
authors.forename: Guido
authors.initials: G
authors.lastname: Van Oost