Cross-tokamak disruption prediction based on domain adaptation

Cross-tokamak disruption prediction based on domain adaptation

The high acquisition cost and the significant demand for disruptive discharges for data-driven disruption prediction models in future tokamaks pose an inherent contradiction in disruption prediction research. In this paper, we demonstrated a novel approach to predict disruption in a future tokamak u...

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Bibliographic Details
Main Authors: Chengshuo Shen, Wei Zheng, Bihao Guo, Yonghua Ding, Dalong Chen, Xinkun Ai, Fengming Xue, Yu Zhong, Nengchao Wang, Biao Shen, Binjia Xiao, Zhongyong Chen, Yuan Pan, J-TEXT Team
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Nuclear Fusion
Subjects:
disruption prediction
cross tokamak
domain adaptation
machine learning
Online Access:https://doi.org/10.1088/1741-4326/ad3e12

Internet

https://doi.org/10.1088/1741-4326/ad3e12

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