3D convolutional and recurrent neural networks in reactor perturbations unfolding and anomaly detection

Leontidis, G. (Speaker)

Activity: Talk, presentation, public lecture, public engagement, outreach and knowledge exchangeInvited talk

Activity

Advanced signal processing methods and learning systems applied to monitor the NPP reactor core condition were the theme of an open workshop organized in cooperation with the European Horizon 2020 CORTEX project in UJV Rez, Czech Republic (https://tinyurl.com/y7rjf63j).

The Workshop, dedicated to nuclear power station research staff, research organizations and academia, was attended by over four dozen experts from 10 European countries, including experts from NPPs, universities, research organizations and the Nuclear Research Institute.

The full-day workshop agenda was divided into 5 sessions, including 14 lectures presented by 10 lecturers.

Description

Dr Leontidis delivered two keynote talks, one focusing on state-of-the-art machine learning methodologies covering recent advancements on deep learning for signal processing. The second talk presented results of Dr Leontidis's lab on detecting anomalies and analysing perturbations in nuclear reactors with machine learning. Both presentations can be found here (https://tinyurl.com/y8eejewr) and here (https://tinyurl.com/y78bepvx)
Period14 Feb 2019
Event titleAdvanced signal processing methods and learning methodologies applied to the monitoring of NPP reactor conditions
Event typeWorkshop
LocationPrague, CZECH REPUBLIC

Keywords

  • Machine Learning
  • Nuclear Reactors