Structural pattern recognition techniques for data retrieval in massive fusion databases

J. Vega, A. Murari, G.A. Rattá, P. Castro, A. Pereira, A. Portas

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

Diagnostics of present day reactor class fusion experiments, like the Joint European Torus (JET), generate thousands of signals (time series and video images) in each discharge. There is a direct correspondence between the physical phenomena taking place in the plasma and the set of structural shapes (patterns) that they form in the signals: bumps, unexpected amplitude changes, abrupt peaks, periodic components, high intensity zones or specific edge contours. A major difficulty related to data analysis is the identification, in a rapid and automated way, of a set of discharges with comparable behavior, i.e. discharges with "similar" patterns. Pattern recognition techniques are efficient tools to search for similar structural forms within the database in a fast an intelligent way. To this end, classification systems must be developed to be used as indexation methods to directly fetch the more similar patterns. © 2008 American Institute of Physics.
Original languageEnglish
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventInternational Conference on Burning Plasma Diagnostics - , Italy
Duration: 1 Jan 2008 → …

Conference

ConferenceInternational Conference on Burning Plasma Diagnostics
CountryItaly
Period1/1/08 → …

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All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

Cite this

Vega, J., Murari, A., Rattá, G. A., Castro, P., Pereira, A., & Portas, A. (2008). Structural pattern recognition techniques for data retrieval in massive fusion databases. Paper presented at International Conference on Burning Plasma Diagnostics, Italy. https://doi.org/10.1063/1.2905118