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Explainable Artificial Intelligence for Identification of Human Errors in Nuclear Power Plants

  • Bhavya Reddy Kotla
  • , Ezgi Gursel
  • , Katy Daniels
  • , Anahita Khojandi
  • , Jamie Baalis Coble
  • , Vivek Agarwal
  • , Vaibhav Yadav
  • , Ronald L. Boring
  • , Mahboubeh Madadi
  • San Jose State University
  • University of Tennessee
  • Idaho National Laboratory

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationProceedings of 13th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, NPIC and HMIT 2023
PublisherAmerican Nuclear Society
Pages1753-1762
Number of pages10
ISBN (Electronic)9780894487910
DOIs
StatePublished - 2023
Externally publishedYes
Event13th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, NPIC and HMIT 2023 - Knoxville, United States
Duration: Jul 15 2023Jul 20 2023

Publication series

SeriesProceedings of 13th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, NPIC and HMIT 2023

Conference

Conference13th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, NPIC and HMIT 2023
Country/TerritoryUnited States
CityKnoxville
Period7/15/237/20/23

ASJC Scopus Subject Areas

  • Human-Computer Interaction
  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Control and Systems Engineering

Keywords

  • anomaly classification
  • LIME
  • nuclear power plants
  • SHAP

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