25 citations · 56 across the 7 of their papers we have counts for
Showing 2022Show all
2 papers · 1 filter
physics.plasm-ph2022★ 2 cited
Transferable Cross-Tokamak Disruption Prediction with Deep Hybrid Neural Network Feature Extractor
Wei Zheng, Fengming Xue, Ming Zhang +12
Predicting disruptions across different tokamaks is a great obstacle to overcome. Future tokamaks can hardly tolerate disruptions at high performance discharge. Few disruption disc…
physics.plasm-ph2022★ 25 cited
IDP-PGFE: An Interpretable Disruption Predictor based on Physics-Guided Feature Extraction
Chengshuo Shen, Wei Zheng, Yonghua Ding +10
Disruption prediction has made rapid progress in recent years, especially in machine learning (ML)-based methods. Understanding why a predictor makes a certain prediction can be as…