中文摘要：

Prediction of disruptions caused by locked modes using the Back-Propagation(BP)neural network is completed on J-TEXT tokamak.The network,which is based on the BP neural network,uses Mirnov coils and locked mode coils signals as input data,and outputs a signal including information of prediction of locked mode.The rate of successful prediction of locked modes is more than 90%.For intrinsic locked mode disruptions,the network can give a prewarning signal about 1 ms ahead of the locking-time.For the disruption caused by resonant magnetic perturbation(RMPs)locked modes,the network can give a prewarning signal about 10 ms ahead of the locking-time.

英文摘要：

Prediction of disruptions caused by locked modes using the Back-Propagation （BP） neural network is completed on J-TEXT tokamak. The network, which is based on the BP neural network, uses Mirnov coils and locked mode coils signals as input data, and outputs a signal including information of prediction of locked mode. The rate of successful prediction of locked modes is more than 90%. For intrinsic locked mode disruptions, the network can give a prewarning signal about 1 ms ahead of the locking-time. For the disruption caused by resonant magnetic perturbation （RMPs） locked modes, the network can give a prewarning signal about 10 ms ahead of the locking-time.