Cluster analysis of the international stellarator confinement database

A. Kus, A. Dinklage, R. Preuss, E. Ascasibar, J. H. Harris, S. Okamura, F. Sano, U. Stroth, J. Talmadge, H. Yamada

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Heterogeneous structure of collected data is one of the problems that occur during derivation of scalings for energy confinement time, and whose analysis tourns out to be wide and complicated matter. The International Stellarator Confinement Database [1], shortly ISCDB, comprises in its latest version 21 a total of 3647 observations from 8 experimental devices, 2067 therefrom beeing so far completed for upcoming analyses. For confinement scaling studies 1933 observation were chosen as the standard dataset. Here we describe a statistical method of cluster analysis for identification of possible cohesive substructures in ISDCB and present some preliminary results.

Original languageEnglish
Title of host publicationPlasma 2007 - Proceedings Intl. Conf. on Research and Applications of Plasmas
Subtitle of host publication4th German-Polish Conference on Plasma Diagnostics for Fusion and Applications
Pages47-50
Number of pages4
DOIs
StatePublished - 2008
EventInternational Conference PLASMA 2007 on Research and Applications of Plasmas: 4th German-Polish Conference on Plasma Diagnostics for Fusion and Applications - 6th French-Polish Seminar on Thermal Plasma in Space and Laboratory - Greifswald, Germany
Duration: Oct 16 2007Oct 19 2007

Publication series

NameAIP Conference Proceedings
Volume993
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

ConferenceInternational Conference PLASMA 2007 on Research and Applications of Plasmas: 4th German-Polish Conference on Plasma Diagnostics for Fusion and Applications - 6th French-Polish Seminar on Thermal Plasma in Space and Laboratory
Country/TerritoryGermany
CityGreifswald
Period10/16/0710/19/07

Keywords

  • 1SS04
  • 1SS95
  • Cluster analysis
  • Hierarchical clustering
  • ISCDB

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