Application of Neural Networks to Plasma Data Analysis
A special issue of Plasma (ISSN 2571-6182).
Deadline for manuscript submissions: 31 January 2026 | Viewed by 193
Special Issue Editor
Interests: plasma physics; neural networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Our understanding of the physics of plasma has been mostly developed using tokamaks. This device is rather complicated, with many unknown variables to control in order for a fusion experiment to begin. Magnetic configuration, internal currents, geometric configuration. There are also various instabilities that should be controlled, including Alfven waves, elms, runaway electrons, and disruptions. All of these issues have been evaluated in various tokamaks and somehow controlled. It is possible to collect all these data and study the most efficient options using a multilayer perceptron, i.e., artificial intelligence.
Prof. Dr. Brunello Tirozzi
Guest Editor
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Keywords
- self-averaging in neural networks
- learning algorithms
- monte carlo simulation for optimization of neural network performance
- critical capacity
- pattern retrieval and recognition
- overlap parameters
- self-organizing maps
- free energy and entropy in neural networks
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