Published September 24, 2005
| Version v1
Report
Graph-based Techniques for Orbit Classification: Early Results
Description
An important step in the quest for low-cost fusion power is the ability to perform and analyze experiments in prototype fusion reactors. An automated analysis and interpretation software toolkit allows physicists to quickly analyze their experiments and plan new ones. In this preliminary report, they consider the analysis of Poincare plots that contain the orbits generated by the particles in a fusion reactor. They describe how they can use graph-based methods to extract features from orbits. These features are then used to evaluate the accuracy of machine learning algorithms and their response on orbits with few points
Availability note (English)
Available from http://www.llnl.gov/tid/lof/documents/pdf/325446.pdf; PURL: https://www.osti.gov/servlets/purl/885147-GDYNSI/Additional details
Identifiers
Publishing Information
- Imprint Pagination
- 41 p.
- Report number
- UCRL-TR--215690
INIS
- Country of Publication
- United States
- Country of Input or Organization
- United States
- INIS RN
- 37095709
- Subject category
- S70: PLASMA PHYSICS AND FUSION TECHNOLOGY; S99: GENERAL AND MISCELLANEOUS;
- Resource subtype / Literary indicator
- Non-conventional Literature
- Descriptors DEI
- ACCURACY; ALGORITHMS; CLASSIFICATION; LEARNING; THERMONUCLEAR REACTORS
- Descriptors DEC
- MATHEMATICAL LOGIC
Optional Information
- Contract/Grant/Project number
- W-7405-ENG-48
- Notes
- PDF-FILE: 41 ; SIZE: 0 KBYTES
- Funding organization
- US Department of Energy (United States)