Adaptive Machine Learning for Robust Diagnostics and Control of Time-Varying Particle Accelerator Components and Beams
Machine learning (ML) is growing in popularity for various particle accelerator applications including anomaly detection such as faulty beam position monitor or RF fault identification, for non-invasive diagnostics, and for creating surrogate models. ML methods such as neural networks (NN) are usefu...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/12/4/161 |