Disruption prediction and model analysis using LightGBM on J-TEXT and HL-2A

Zhong, Y; Zheng, W; Chen, ZY; Xia, F; Yu, LM; Wu, QQ; Ai, XK; Shen, CS; Yang, ZY; Yan, W; Ding, YH; Liang, YF; Chen, ZP; Tong, RH; Bai, W; Fang, JG; Li, F

Zheng, W; Chen, ZY (corresponding author), Huazhong Univ Sci & Technol, State Key Lab Adv Electromagnet Engn & Technol, Int Joint Res Lab Magnet Confinement Fus & Plasma, Sch Elect & Elect Engn, Wuhan 430074, Peoples R China.; Chen, ZY (corresponding author), Chengdu Univ, Chengdu 610106, Peoples R China.

PLASMA PHYSICS AND CONTROLLED FUSION, 2021; 63 (7):

Abstract

Using machine learning (ML) techniques to develop disruption predictors is an effective way to avoid or mitigate the disruption in a large-scale tokam......

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