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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