False Sensor-Data Detection Strategy for the Post-Hazard Condition Monitoring of Nuclear Systems using Statistical Approaches and Long Short-term Memory

Simple item page
dc.contributor.authorJoomyung Lee
dc.contributor.authorHarleen Kaur Sandhu
dc.contributor.authorSaran Srikanth Bodda
dc.contributor.authorAbhinav Gupta
dc.contributor.authorNam Dinh
dc.date.accessioned2024-11-25T22:18:53Z
dc.date.available2024-11-25T22:18:53Z
dc.date.issued2024-03-03
dc.identifier.urihttps://www.lib.ncsu.edu/resolver/1840.20/44938
dc.publisherIASMiRT
dc.relation.ispartofseriesDivision 12 - New Technologies (Additive Manufacturing, AI, Digital Twin, etc.)
dc.relation.ispartofseriesDivision 12-Tu.3.K - AI and Deep Learning Application (2)
dc.relation.ispartofseries00 - SMiRT 27 - Yokohama, Japan. March 3-8, 2024
dc.titleFalse Sensor-Data Detection Strategy for the Post-Hazard Condition Monitoring of Nuclear Systems using Statistical Approaches and Long Short-term Memory
dc.typeConference Proceeding

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Tu.3.K-04.pdf
Size:
4.93 MB
Format:
Adobe Portable Document Format
Download

Collections

2024 - SMiRT 27 - Yokohama, Japan