Development of machine learning techniques and evaluation of analysis results

Stefanos Kollias, Andreas Stafylopatis, Georgios Leontidis, Georgios Alexandridis, Tatiana Tabouratzis, Aiden Mark Durrant

Research output: Other contribution


This document outlines and describes the development of deep neural network architectures and other machine learning
techniques for the unfolding of reactor transfer functions from in-core and ex-core neutron detectors, developed in CORTEX
Workpackage 3, mainly in Task 3.3. The techniques developed utilise simulated modelling of the induced neutron flux of
perturbations to classify and localise perturbation types and their sources.
Original languageEnglish
PublisherEuropean Commission
Number of pages42
Publication statusPublished - 12 Aug 2019


  • nuclear reactors
  • Machine learning


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