An Interpretable Time Series Data Prediction Framework for Severe Accidents in Nuclear Power Plants

Accurately predicting severe accident data in nuclear power plants is of utmost importance for ensuring their safety and reliability. However, existing methods often lack interpretability, thereby limiting their utility in decision making. In this paper, we present an interpretable framework, called...

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Detalles Bibliográficos
Autores principales: Fu, Yongjie, Zhang, Dazhi, Xiao, Yunlong, Wang, Zhihui, Zhou, Huabing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453600/
https://www.ncbi.nlm.nih.gov/pubmed/37628190
http://dx.doi.org/10.3390/e25081160

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453600/
https://www.ncbi.nlm.nih.gov/pubmed/37628190
http://dx.doi.org/10.3390/e25081160

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