Automatic determination of L/H transition times in DIII-D through a collaborative distributed environment

An automatic predictor of L/H transition times has been implemented for the DIII-D tokamak. The system predicts the transition combining two techniques: A morphological pattern recognition algorithm, which estimates the transition based on the waveform of a Dα emission signal, and a support vector machines multi-layer model, which predicts the L/H transition using a non-parametric model. The predictor is employed within a collaborative distributed computing environment. The system is trained remotely in the Ciemat computer cluster and operated on the DIII-D site.