izvor podataka: crosbi
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Targeting and synchronization at tokamak with recurrent artificial neural networks (CROSBI ID 168911)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Rastović, Danilo
Targeting and synchronization at tokamak with recurrent artificial neural networks // Neural computing and applications, 21 (2012), 5; 1065-1069. doi: 10.1007/s00521-011-0527-4
Podaci o odgovornosti
Rastović, Danilo
engleski
Targeting and synchronization at tokamak with recurrent artificial neural networks
In this letter, we propose an adaptive recurrent artificial neural networks synchronization of H-mode and Edge Localized Modes that is important for obtaining a long pulse tokamak without disruption regime. The deterministic part of the plasma behavior should be synchronized with stochastic part by introducing stochastic artificial neural network.
tokamak; synchronization; recurrent artificial neural networks
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Podaci o izdanju
21 (5)
2012.
1065-1069
objavljeno
0941-0643
10.1007/s00521-011-0527-4
Povezanost rada
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