Unbiased and non-supervised learning methods for disruption prediction at JET
Author:
Publisher
IOP Publishing
Subject
Condensed Matter Physics,Nuclear and High Energy Physics
Reference22 articles.
1. Disruptions in tokamaks
2. Neural network prediction of some classes of tokamak disruptions
3. Forecast of TEXT plasma disruptions using soft X rays as input signal in a neural network
4. Forecasting disruptions in the ADITYA tokamak using neural networks
5. Tokamak disruption alarm based on a neural network model of the high- beta limit
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