Poster Open Access

3D convolutional and recurrent neural networks for reactor perturbation unfolding and anomaly detection

Durrant A.; Leontidis G.; Kollias S.


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  "description": "<p>Poster on&nbsp;3D convolutional and recurrent neural networks for reactor perturbation unfolding and anomaly detection at&nbsp;9th European Commission Conferences on EURATOM Research and Training in Safety of Reactor Systems and Radioactive Waste Management (FISA 2019 - Euradwaste&rsquo; 19)</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "University of Lincoln", 
      "@type": "Person", 
      "name": "Durrant A."
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    {
      "affiliation": "University of Lincoln", 
      "@type": "Person", 
      "name": "Leontidis G."
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    {
      "affiliation": "University of Lincoln", 
      "@type": "Person", 
      "name": "Kollias S."
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  "url": "https://zenodo.org/record/3243887", 
  "datePublished": "2019-06-07", 
  "@type": "CreativeWork", 
  "keywords": [
    "Reactor safety, modeling, CORTEX"
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  "identifier": "https://doi.org/10.5281/zenodo.3243887", 
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  "name": "3D convolutional and recurrent neural networks for reactor perturbation unfolding and anomaly detection"
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