J.-TEXT team

According to our database, J.-TEXT team authored at least 4 papers between 2022 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2023

Extraction of n = 0 pick-up by locked mode detectors based on neural networks in J-TEXT.

Chengshuo Shen, Jianchao Li, Yonghua Ding, Jiaolong Dong, Nengchao Wang, Dongliang Han, Feiyue Mao, Da Li, Zhipeng Chen, Zhoujun Yang, Zhongyong Chen, Yuan Pan, J.-TEXT team

CoRR, 2023

Feature-based Transferable Disruption Prediction for future tokamaks using domain adaptation.

Chengshuo Shen, Wei Zheng, Bihao Guo, Dalong Chen, Xinkun Ai, Fengming Xue, Yu Zhong, Nengchao Wang, Biao Shen, Binjia Xiao, Yonghua Ding, Zhongyong Chen, Yuan Pan, J.-TEXT team

CoRR, 2023

Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection.

Xinkun Ai, Wei Zheng, Ming Zhang, Dalong Chen, Chengshuo Shen, Bihao Guo, Bingjia Xiao, Yu Zhong, Nengchao Wang, Zhoujun Yang, Zhipeng Chen, Zhongyong Chen, Yonghua Ding, Yuan Pan, J.-TEXT team

CoRR, 2023

2022

IDP-PGFE: An Interpretable Disruption Predictor based on Physics-Guided Feature Extraction.

Chengshuo Shen, Wei Zheng, Yonghua Ding, Xinkun Ai, Fengming Xue, Yu Zhong, Nengchao Wang, Li Gao, Zhipeng Chen, Zhoujun Yang, Zhongyong Chen, Yuan Pan, J.-TEXT team

CoRR, 2022