Research on wind power prediction by integrating multi-scale decomposition and migration-enhanced deep learning architecture
With the rapid development of renewable energy, wind-power forecasting faces core challenges of strong volatility and non-stationarity, and traditional methods no longer meet accuracy requirements. To address this, a hybrid model, STL-HHO-BMGTL-OSRELM (SHBO), is proposed, integrating decomposition,...
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| Główni autorzy: | , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
AIP Publishing LLC
2025-09-01
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| Seria: | AIP Advances |
| Dostęp online: | http://dx.doi.org/10.1063/5.0287617 |
| Etykiety: |
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