Application of cost-sensitive LSTM in water level prediction for nuclear reactor pressurizer

Application of cost-sensitive LSTM in water level prediction for nuclear reactor pressurizer

Applying an accurate parametric prediction model to identify abnormal or false pressurizer water levels (PWLs) is critical to the safe operation of marine pressurized water reactors (PWRs). Recently, deep-learning-based models have proved to be a powerful feature extractor to perform high-accuracy p...

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Bibliographic Details
Main Authors: Jin Zhang, Xiaolong Wang, Cheng Zhao, Wei Bai, Jun Shen, Yang Li, Zhisong Pan, Yexin Duan
Format: Article
Language:English
Published: Elsevier 2020-07-01
Series:Nuclear Engineering and Technology
Subjects:
LSTM
Parameter prediction
Cost sensitive
Pressurizer
Pressurized water reactor
Time series
Online Access:http://www.sciencedirect.com/science/article/pii/S1738573319304218

Internet

http://www.sciencedirect.com/science/article/pii/S1738573319304218

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