Energy Threshold Detection in Neutronic Signal by Automatic Classification and Linear Programming

Philippe Durand 1 Luan Jaupi 2 Dariush Ghorbanzadeh 3
1 M2N - Modélisation mathématique et numérique
2 CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage
CEDRIC - Centre d'études et de recherche en informatique et communications
3 CEDRIC - LAETITIA - CEDRIC. Traitement du signal et architectures électroniques
CEDRIC - Centre d'études et de recherche en informatique et communications
Abstract : It is proposed in this paper the automatic detection thresholds in the neutronic noise from a nuclear reactor chamber. The proposed method combines a pattern recognition algorithm, known as dynamic cluster and a linear programming algorithm. Euclidean distance, often adopted by default, in the dynamic cluster algorithm; is here replaced by the distance L 1 , also called least absolute deviations (LAD).
Keywords : Index Terms-EMC Dynamic Cluster Algorithm Linear Programming Neutronic noise
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Philippe Durand, Luan Jaupi, Dariush Ghorbanzadeh. Energy Threshold Detection in Neutronic Signal by Automatic Classification and Linear Programming. World Congress on Engineering 2015, IAENG, Jul 2015, London, United Kingdom. pp.86-89. ⟨hal-02464414⟩

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