Predicting the Onset of Plasma Disruptions in Tokamaks Using Artificial Neural Networks
نویسندگان
چکیده
Artificial neural networks are computer algorithms that simulate, in a very simplified form, the ability of brain neurons to process information. Basically, within each unit of the network, all the input weighted signals are summed and an excitatory or inhibitory signal is then fired to the next layer's units (Fig. 1). The training of the neural net is performed by adjusting the weights between each connection as to minimize the error during the prediction processes ("back propagation") [1,2]. Fig. 1 – Feed-forward neural network showing the weighted connections between all the neurons units. II Basic Idea
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