This paper describes the implementation of a real-time disruption predictor that is based on support vector machine (SVM) classifiers. The implementation was performed under the MARTe framework on a six-core x86 architecture. The system is connected via JET's Real-time Data Network (RTDN). The online results show a high degree of successful predictions and a low rate of false alarms, thus confirming the usefulness of this approach in a disruption mitigation scheme. The implementation shows a low computational load, which will be exploited in the immediate future to increase the prediction's temporal resolution.

Implementation of the Disruption Predictor APODIS in JET's Real-Time Network Using the MARTe Framework

Murari A;
2014

Abstract

This paper describes the implementation of a real-time disruption predictor that is based on support vector machine (SVM) classifiers. The implementation was performed under the MARTe framework on a six-core x86 architecture. The system is connected via JET's Real-time Data Network (RTDN). The online results show a high degree of successful predictions and a low rate of false alarms, thus confirming the usefulness of this approach in a disruption mitigation scheme. The implementation shows a low computational load, which will be exploited in the immediate future to increase the prediction's temporal resolution.
2014
Istituto gas ionizzati - IGI - Sede Padova
Inglese
61
2
741
744
4
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6782334
Sì, ma tipo non specificato
Machine learning
Real time systems
Learning systems
False alarms
Low computational loads
Low rates
Mitigation schemes
Real-time data
Real-time networks
Temporal resolution
Support vector machines
This work was supported in part by the Spanish Ministry of Science and Innovation under the Projects ENE2008-02894/FTN and ENE2009-10280 and carried out within the framework of the European Fusion Development Agreement. / IEEE transactions on nuclear science (Online) - Paese di pubblicazione: Stati Uniti d'America - Lingua: inglese - e-Issn: 1558-1578 - Titolo chiave: IEEE transactions on nuclear science (Online) - Titolo proprio: IEEE transactions on nuclear science (Online) - Titolo abbreviato: IEEE trans. on nucl. sci. (Online) - Titoli alternativi: Transactions on nuclear science (Online) Nuclear science (Online) Nuclear medical and imaging sciences (NMIS) (Online)
9
info:eu-repo/semantics/article
262
Lopez, Jm; Vega, J; Alves, D; Dormidocanto, S; Murari, A; Ramirez, Jm; Felton, R; Ruiz, M; De Arcas, G
01 Contributo su Rivista::01.01 Articolo in rivista
none
   Implementation of activities described in the Roadmap to Fusion during Horizon 2020 through a Joint programme of the members of the EUROfusion consortium
   EUROfusion
   H2020
   633053
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/255555
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