Cargando…
STUDY OF FEASIBILITY AND USEFULNESS OF MACHINE LEARNING METHODS TO HELP IDENTIFYING RESIDUAL GAS COMPOSITION
This report summarizes the outcome of the collaboration between CERN and Intelligent Data Analysis Laboratory (IDAL). In this feasibility study we investigated the potential usefulness of machine-learning applications to identify residual gas compositions. The report focus on the performance of the...
| Autores principales: | , |
|---|---|
| Lenguaje: | eng |
| Publicado: |
2018
|
| Materias: | |
| Acceso en línea: | http://cds.cern.ch/record/2740627 |