In modern thermonuclear fusion devices it is possible to distinguish distinct types of plasma confinement regimes which have different performance in terms of confinement time. Discriminating among them could represent a useful feature for an efficient control of a plasma experiment. An automatic identifier based on fuzzy logic is here proposed together with an unsupervised technique, using classification and regression trees, for selecting, among several diagnostic signals available, the inputs to be provided to the identifier.
|Publication status||Published - 2008|
|Event||16th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning, ESANN 2008 - , Belgium|
Duration: 1 Jan 2008 → …
|Conference||16th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning, ESANN 2008|
|Period||1/1/08 → …|
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Information Systems
Vagliasindi, G., Arena, P., Fortuna, L., Murari, A., Mazzitelli, G., Gallo, A., & Vagliasindi, U. (2008). An automatic identifier of confinement regimes at JET combining fuzzy logic and classification trees. Paper presented at 16th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning, ESANN 2008, Belgium.