Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Jingke She"'
Publikováno v:
Frontiers in Nuclear Engineering, Vol 3 (2024)
A novel deep learning model zLSTM, which evolves from Long-Short Term Memory (LSTM) with enhanced long-term processing capability, is applied to the prediction of Loss of Coolant Accident (LOCA). During the prediction process, six-dimensional multiva
Externí odkaz:
https://doaj.org/article/80e2a40dc9bb463ca30ca8935c0e2cd8
Publikováno v:
Frontiers in Energy Research, Vol 11 (2023)
A deep learning-based multi-node framework is constructed in this work to provide a data-driven platform that provides predictions for the operation condition of the primary heat transfer (PHT) loop in nuclear power plants (NPPs). Several deep learni
Externí odkaz:
https://doaj.org/article/67fac3f6e8764cffac34f3442bad9209
Publikováno v:
IEEE Access, Vol 9, Pp 49007-49015 (2021)
The rapid development of the IoT and cloud computing has spawned a new network structure — sensor-cloud system (SCS) where sensors, sensor networks, and cloud computing are integrated to perform data sensing, collection, transmission, and decision
Externí odkaz:
https://doaj.org/article/6bf8eb3f919e49ceaf0dc727ac06e940
Publikováno v:
Frontiers in Energy Research, Vol 10 (2022)
Post-LOCA prediction is of safety significance to NPP, but requires a processing coverage of non-linearity, both short and long-term memory, and multiple system parameters. To enable an ability promotion of previous LOCA prediction models, a new gate
Externí odkaz:
https://doaj.org/article/dbc4faa3bdf34b019806ac4d75cd3dc9
Publikováno v:
Frontiers in Energy Research, Vol 9 (2021)
A combination of Convolutional Neural Network (CNN), Long-Short Term Memory (LSTM), and Convolutional LSTM (ConvLSTM) is constructed in this work for the fault diagnosis and post-accident prediction for Loss of Coolant Accidents (LOCAs) in Nuclear Po
Externí odkaz:
https://doaj.org/article/af3d6f557ebd488dad20438cc61a6c1a
Publikováno v:
Computer Science and Education ISBN: 9789819924455
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ccd9b519f1313e66e8bc0c8d4b6b42c0
https://doi.org/10.1007/978-981-99-2446-2_28
https://doi.org/10.1007/978-981-99-2446-2_28
Publikováno v:
2022 International Joint Conference on Neural Networks (IJCNN).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14c64dff1c41140901606819393c9d5f
https://doi.org/10.1109/ijcnn55064.2022.9889794
https://doi.org/10.1109/ijcnn55064.2022.9889794
Publikováno v:
2022 International Joint Conference on Neural Networks (IJCNN).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50526b6d6ebdb23dd3ea5026982febc6
https://doi.org/10.1109/ijcnn55064.2022.9892346
https://doi.org/10.1109/ijcnn55064.2022.9892346
Publikováno v:
IEEE Access, Vol 9, Pp 49007-49015 (2021)
The rapid development of the IoT and cloud computing has spawned a new network structure — sensor-cloud system (SCS) where sensors, sensor networks, and cloud computing are integrated to perform data sensing, collection, transmission, and decision
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a14c1f4ffff1fe9e1409b32b792f022b
https://ieeexplore.ieee.org/document/9386062/
https://ieeexplore.ieee.org/document/9386062/
Publikováno v:
2021 International Conference on Computational Science and Computational Intelligence (CSCI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed9bd448d6507bcab07966a99d61246b
https://doi.org/10.1109/csci54926.2021.00032
https://doi.org/10.1109/csci54926.2021.00032