A Comparison between Soft Computing and Statistic Approaches to Identify Plasma Columns in Tokamak Reactors
Salvatore Calcagno, Antonino Greco, Francesco Carlo Morabito, Mario Versaci · The 2006 IEEE International Joint Conference on Neural Network Proceedings · 2006
This paper is concerned with the application of novel techniques of data interpretation for reconstructing plasma shape in Tokamak reactors for nuclear fusion applications. In particular, Artificial Neural Networks have been taken into account to estimate the distance of the plasma boundary from the fist wall of the vacuum vessel in ITER configuration. In addition, a comparison with Principal Component Analysis and Functional Parameterization is presented. Finally, in order to reduce the computational complexity, non linear techniques for ranking sensors is exploited.