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Machine learning for early fault detection in accelerator systems
With the development of systems based on a combination of mechanics, electronics and – more and more - software components, increasing system complexity is a de facto trend in the engineering world. Particle accelerators make no exception to this paradigm. The continuous push for higher energies dri...
Autores principales: | Apollonio, Andrea, Cartier-Michaud, Thomas, Felsberger, Lukas, Mueller, Andreas, Todd, Benjamin |
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Lenguaje: | eng |
Publicado: |
2020
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2706468 |
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