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2007.01401
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Hybrid deep learning architecture for general disruption prediction across tokamaks
2 July 2020
J. Zhu
Cristina Rea
K. Montes
R. Granetz
R. Sweeney
R. A. Tinguely
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Papers citing
"Hybrid deep learning architecture for general disruption prediction across tokamaks"
4 / 4 papers shown
Title
Fast Dynamic 1D Simulation of Divertor Plasmas with Neural PDE Surrogates
Y. Poels
G. Derks
E. Westerhof
Koen Minartz
Sven Wiesen
Vlado Menkovski
3DGS
AI4CE
84
18
0
30 May 2023
Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection
X. Ai
W. Zheng
Ming Zhang
Dalong Chen
C. Shen
...
Zhipeng Chen
Zhongyong Chen
Yonghua Ding
Y. Pan
J-Text Team
31
3
0
27 Mar 2023
Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks
J. Zhu
C. Rea
R. Granetz
E. Marmar
K. Montes
...
B. Shen
B. Xiao
D. Humphreys
J. Barr
O. Meneghini
30
17
0
18 Sep 2021
Experiment data-driven modeling of tokamak discharge in EAST
Chenguang Wan
Jian-gang Li
Zhi Yu
Xiaojuan Liu
31
17
0
21 Jul 2020
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