Actions for Graph-based Methods for Orbit Classification [electronic resource].

Email RIS file
Bookmark
Report an Issue

Graph-based Methods for Orbit Classification [electronic resource].

Published
Washington, D.C. : United States. Dept. of Energy, 2005.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description
PDF-file: 14 pages; size: 0 Kbytes
Additional Creators
Lawrence Berkeley National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
Access Online

Availability

I Want It
I Want It

Finding items...

Restrictions on Access
Free-to-read Unrestricted online access
Summary
An important step in the quest for low-cost fusion power is the ability to perform and analyze experiments in prototype fusion reactors. One of the tasks in the analysis of experimental data is the classification of orbits in Poincare plots. These plots are generated by the particles in a fusion reactor as they move within the toroidal device. In this paper, we describe the use of graph-based methods to extract features from orbits. These features are then used to classify the orbits into several categories. Our results show that existing machine learning algorithms are successful in classifying orbits with few points, a situation which can arise in data from experiments.
Report Numbers
E 1.99:ucrl-conf-215802
ucrl-conf-215802
Subject(s)
Other Subject(s)
Note
Published through SciTech Connect.
09/29/2005.
"ucrl-conf-215802"
Presented at: SIAM International Conference on Data Mining, Bethesda, MD, United States, Apr 20 - Apr 22, 2006.
Kamath, C; Bagherjeiran, A.
Funding Information
W-7405-ENG-48
View MARC record | catkey: 14739086