Streamlining hyperparameter optimization for radiation emulator training with automated Sherpa
Abstract This study aimed to identify the optimal configuration for neural network (NN) emulators in numerical weather prediction, minimizing trial and error by comparing emulator performance across multiple hidden layers (1–5 layers), as automatically defined by the Sherpa library. Our findings rev...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-04-01
|
| Series: | Geoscience Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40562-024-00336-8 |