Yang, Zongyu https://orcid.org/0009-0000-4083-1552
Zhong, Wulyu https://orcid.org/0000-0001-8217-9400
Xia, Fan
Gao, Zhe https://orcid.org/0000-0003-0275-6330
Zhu, Xiaobo https://orcid.org/0009-0004-2762-7038
Li, Jiyuan
Hu, Liwen
Xu, Zhaohe
Li, Da
Zheng, Guohui
Chen, Yihang
Zhang, Junzhao
Li, Bo
Zhang, Xiaolong
Zhu, Yiren
Tong, Ruihai
Dong, Yunbo
Zhang, Yipo
Yuan, Boda
Yu, Xin
He, Zongyuhui
Tian, Wenjing https://orcid.org/0009-0009-3172-3512
Gong, Xinwen
Funding for this research was provided by:
National Natural Science Foundation of China (U21A20440)
Sichuan Province Innovative Talent Funding Project for Postdoctoral fellows (BX202222)
National MCF R&D program of China (2019YFE03010003)
Article Title: Implementing deep learning-based disruption prediction in a drifting data environment of new tokamak: HL-3
Journal Title: Nuclear Fusion
Article Type: paper
Copyright Information: © 2025 The Author(s). Published by IOP Publishing Ltd on behalf of the IAEA
Publication dates
Date Received: 2024-03-19
Date Accepted: 2024-12-26
Online publication date: 2025-01-07