HL-2A tokamak disruption forecasting based on an
artificial neural network
Wang Hao;Wang Ai-Ke;Yang Qing-Wei;Ding Xuan-Tong;Dong Jia-Qi;Sanuki H;Itoh K
【期刊名称】《中国物理：英文版》 【年(卷),期】2007(016)012
【摘要】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 possibiliry of developing a neural network predictor that intervenes well in edvance for avoiding plasma disruption or mitigating its effects. 【总页数】4页(3738-3741)
【关键词】disruption, prediction, artificial neural networks
【作者】Wang Hao;Wang Ai-Ke;Yang Qing-Wei;Ding Xuan-Tong;Dong Jia-Qi;Sanuki H;Itoh K
【作者单位】Southwestern Institute of Physic, Chengdu 610041, China;Southwestern China;Southwestern China;Southwestern
Institute Institute Institute
of of of
Physic, Physic, Physic,
Chengdu Chengdu Chengdu
610041, 610041, 610041,
China;Southwestern Institute of Physic, Chengdu 610041, China;National
HL-2A tokamak disruption forecasting based on an artificial neural network
