Interpretable Time Series Data Prediction for Severe Nuclear Accidents-Reference-Cited by-同舟云学术

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Interpretable Time Series Data Prediction for Severe Nuclear Accidents

Published:2023-11-24 Issue: Volume:1 Page:574-580
ISSN:
Container-title:2023 3rd International Conference on New Energy and Power Engineering (ICNEPE)
language:
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Author:

Zhang Dazhi¹,Jiang Mengyuan²,Fu Yongjie²,Zhou Huabing²

Affiliation:

1. China Nuclear Power Operation Technology Corporation, Ltd,CNNC Key Laboratory on Nuclear Industry Simulation,Wuhan,China,430040

2. Wuhan Institute of Technology Hubei Provincial Key Laboratory of Intelligent Robot, Wuhan Institute of Technology,College of Computer Science and Engineering,Wuhan,China,430205

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10428934/10429048/10429373.pdf?arnumber=10429373

Reference13 articles.

1. Prediction of Leak Flow Rate Using Fuzzy Neural Networks in Severe Post-LOCA Circumstances

2. Estimation of LOCA Break Size Using Cascaded Fuzzy Neural Networks

3. Critical flow prediction using simplified cascade fuzzy neural networks

4. Advanced fault diagnosis method for nuclear power plant based on convolutional gated recurrent network and enhanced particle swarm optimization

5. Prediction of Leak Flow Rate Using Fuzzy Neural Networks in Severe Post-LOCA Circumstances

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