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Using neural networks to speed up optimization algorithms
The paper presents the application of radial-basis-function (RBF) neural networks to speed up deterministic search algorithms used for the design and optimization of superconducting LHC magnets. The optimization of the iron yoke of the main dipoles requires a number of numerical field computations p...
| Autores principales: | , |
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| Lenguaje: | eng |
| Publicado: |
2000
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1051/epjap:2000177 http://cds.cern.ch/record/502990 |