title: A classification scheme for edge-localized modes based on their probability distributions.
abstract: We present here an automated classification scheme which is particularly well suited to scenarios where the parameters have significant uncertainties or are stochastic quantities. To this end, the parameters are modeled with probability distributions in a metric space and classification is conducted using the notion of nearest neighbors. The presented framework is then applied to the classification of type I and type III edge-localized modes (ELMs) from a set of carbon-wall plasmas at JET. This provides a fast, standardized classification of ELM types which is expected to significantly reduce the effort of ELM experts in identifying ELM types. Further, the classification scheme is general and can be applied to various other plasma phenomena as well.
authors.affiliation: Department of Applied Physics, Ghent University, B-9000 Ghent, Belgium.
authors.forename: A
authors.initials: A
authors.lastname: Shabbir
authors.affiliation: Department of Applied Physics, Ghent University, B-9000 Ghent, Belgium.
authors.forename: G
authors.initials: G
authors.lastname: Hornung
authors.affiliation: Department of Applied Physics, Ghent University, B-9000 Ghent, Belgium.
authors.forename: G
authors.initials: G
authors.lastname: Verdoolaege
authors.affiliation: EUROfusion Consortium, JET, Culham Science Centre, Abingdon OX14 3DB, United KingdomDepartment of Applied Physics, Ghent University, B-9000 Ghent, BelgiumMax Planck Institute for Plasma Physics, D-85748 Garching, GermanyLaboratory for Plasma Physics, Royal Military Academy, B-1000 Brussels, Belgium.