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physics.plasm-ph2026
Machine learning prediction of plasma behavior from discharge configurations on WEST
Chenguang Wan, Feda Almuhisen, Philippe Moreau +10
Accurately predicting plasma behavior based on discharge configurations is essential for the safe and efficient operation of tokamak experiments. While physics-based integrated mod…
physics.plasm-ph2024
Attention-aware convolutional neural networks for identification of magnetic islands in the tearing mode on EAST tokamak
Feifei Long, Yian Zhao, Yunjiao Zhang +16
The tearing mode, a large-scale MHD instability in tokamak, typically disrupts the equilibrium magnetic surfaces, leads to the formation of magnetic islands, and reduces core elect…
physics.plasm-ph2024
Reconstruction of Poloidal Magnetic Fluxes on EAST based on Neural Networks with Measured Signals
Feifei Long, Xiangze Xia, Jian Liu +9
The accurate construction of tokamak equilibria, which is critical for the effective control and optimization of plasma configurations, depends on the precise distribution of magne…