Xinkun Ai

According to our database, Xinkun Ai authored at least 5 papers between 2022 and 2023.

Collaborative distances:

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

2023

Ball Mill Fault Prediction Based on Deep Convolutional Auto-Encoding Network.

Xinkun Ai, Kun Liu, Wei Zheng, Yonggang Fan, Xinwu Wu, Peilong Zhang, Liye Wang, JanFeng Zhu, Yuan Pan

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

Transferable Cross-Tokamak Disruption Prediction with Deep Hybrid Neural Network Feature Extractor.

Wei Zheng, Fengming Xue, Ming Zhang, Zhongyong Chen, Chengshuo Shen, Xinkun Ai, Nengchao Wang, Dalong Chen, Bihao Guo, Yonghua Ding, Zhipeng Chen, Zhoujun Yang, Biao Shen, Bingjia Xiao, Yuan Pan

CoRR, 2022