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HL-2A tokamak disruption forecasting based on an artificial neural network |
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| Authors: | Wang Hao Wang Ai-Ke Yang Qing-Wei Ding Xuan-Tong Dong Jia-Qi Sanuki H and Itoh K |
| Affiliation: | Southwestern Institute of Physics, Chengdu 610041, China; National Institute for Fusion Science, Toki, Gifu, 509-5292, Japan |
| Abstract: | Artificial neural networks are trained to forecast the plasma disruption in HL-2A tokamak. Optimized network architecture is obtained. Saliency analysis is made to assess the relative importance of different diagnostic signals as network input. The trained networks can successfully detect the disruptive pulses of HL-2A tokamak. The results obtained show the possibility of developing a neural network predictor that intervenes well in advance for avoiding plasma disruption or mitigating its effects. |
| Keywords: | disruption prediction artificial neural networks |
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