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An improved method using radial basis function neural networks to speed up optimization algorithms
The paper presents a method using radial basis function (RBF) neural networks to speed up deterministic search algorithms used for the optimization of superconducting magnets for the LHC accelerator project at CERN. The optimization of the iron yoke of the main LHC dipoles requires a number of numer...
| Autores principales: | , , |
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| Lenguaje: | eng |
| Publicado: |
2002
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1109/20.996277 http://cds.cern.ch/record/560344 |