Fuzzy logic and support vector machine approaches to regime identification in JET

A plasma regime is a distinct type of plasma confinement, which can be identified from several conventional plasma diagnostic signals. An accurate and general regime identifier is considered an important tool for future real time applications in Joint European Torus (JET). In this perspective, a traditional approach based on Discriminant Analysis was tested, using various sets of JET real time signals. Unfortunately, no combination of signals managed to provide a success rate higher than 90%. To improve the performance and increase the generalization capability, an identifier based on Fuzzy Logic was developed, which allowed inclusion of the time evolution of the D
_alpha
, a quantity normally not exploited by more traditional solutions. With this technique a success rate of 95% was achieved using only D
_alpha
and the derivative of betaN diamagnetic as inputs. A support vector machines approach, based again on a suitably defined distance like discriminant analysis, provided slightly inferior results with exactly the same inputs but matched the fuzzy logic method with the inclusion of the absolute value of beta
_N
diamagnetic. This comparative performance assessment of the various methods is an important first step on the route to identify the best solution for a regime identifier for JET and in due course for ITER