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

Academic Article
Publication Date:
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.
Iris type:
01.01 Articolo in rivista
Keywords:
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
List of contributors:
Murari, Andrea
Authors of the University:
MURARI ANDREA
Handle:
https://iris.cnr.it/handle/20.500.14243/255555
Published in:
IEEE TRANSACTIONS ON NUCLEAR SCIENCE
Journal
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URL

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6782334
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