CONFINEMENT REGIME IDENTIFICATION AT JET VIA AN INTERPRETABLE FUZZY LOGIC CLASSIFIER

In this paper a data driven methodology to automat- ically derive an interpretable Fuzzy Logic Classifier (FLC) has been applied to the problem of confinement regime identification in the Joint European Torus. The approach has been developed explicitly to handle with the complexities of the inference process in Magnetic Confinement Nuclear Fusion (MCNF). The first step of the method consists of a supervised, exploratory anal- ysis performed with the approach of Classification and Regression Trees (CART), to extract the variables in the database which are the most critical for the prob- lem under study. Then, a fully automated algorithm determines the membership functions and the most ap- propriate rules to reproduce the classification tree ob- tained with CART. The resulting FLI on the one hand attains very good performance in terms of generaliza- tion and classification, on the other hand provides a se- ries of rules which can be easily interpreted and con- tributing to a very good first, intuitive understanding of the physics involved.