Abstract
The accurate assessment of human error probability (HEP) has an important impact on the safety of nuclear power plants. Therefore, it is necessary to develop a HEP model. This study analyzes the validity, sensitivity, and relationship between HEP and the indices of eye response and the subjective rating method. The analysis result showed that there is a correlation between HEP and the indices of eye response, subjective workload, and situation awareness level. Therefore, a back propagation neural network model was developed based on these indices. The correlation coefficient is more than 0.95 between the predicted data of the developed model and the target data. Also, the root mean square error was 0.0073, 0.0083, and 0.0077, and the determination coefficient was 0.965, 0.933, and 0.931 for the training, validation, and testing data sets, respectively. Therefore, the developed back propagation neural network model has reliable prediction accuracy for HEP.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.