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

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).
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Dates and versions

hal-02464414 , version 1 (11-02-2020)

Identifiers

  • HAL Id : hal-02464414 , version 1

Cite

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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