Neuro-fuzzy estimation of plasma boundary in ITER configuration

In this paper a soft computing approach to estimate the distances of the plasma boundary from the first wall of the vacuum vessel in ITER machine is carried out. In particular, neuro-fuzzy inference systems are exploited in order to reconstruct the plasma shape starting from magnetic measurements. In order to build a manageable system, we exploit a nonlinear technique of ranking magnetic sensors.