DESIGNING AN IMPROVED NEURAL NETWORK FOR THE EARLY DETECTION OF ANOMALIES IN NUCLEAR POWER PLANTS
The effectiveness and dependability of these vital energy infrastructures depend heavily on the early detection of anomalies in nuclear power plants (NPPs). Anomalies in a plant's operations might be signs of the impending equipment failure, a danger to workers' safety, or departure from i...
Main Authors: | Solomon Jebaraj, Davendra Kumar Doda, Vineet Saxena |
---|---|
Format: | Article |
Language: | English |
Published: |
University of Kragujevac
2023-08-01
|
Series: | Proceedings on Engineering Sciences |
Subjects: | |
Online Access: | https://pesjournal.net/journal/v5-nS1/9.pdf |
Similar Items
-
Network Security Situation Prediction Based on Optimized Clock-Cycle Recurrent Neural Network for Sensor-Enabled Networks
by: Xiuli Du, et al.
Published: (2023-07-01) -
FEB-Stacking and FEB-DNN Models for Stock Trend Prediction: A Performance Analysis for Pre and Post Covid-19 Periods
by: Indranil Ghosh, et al.
Published: (2021-02-01) -
Anomaly Detection Model of Network Dataflow Based on an Improved Grey Wolf Algorithm and CNN
by: Liting Wang, et al.
Published: (2023-09-01) -
Body-Worn Sensors for Recognizing Physical Sports Activities in Exergaming via Deep Learning Model
by: Mir Mushhood Afsar, et al.
Published: (2023-01-01) -
A Dynamic Branch Predictor Based on Parallel Structure of SRNN
by: Lei Zhang, et al.
Published: (2020-01-01)