Minimalist Deep Learning for Solar Power Forecasting: Transformer-Based Prediction Using Key Meteorological Features
Solar power forecasting is important for energy management and grid stability, yet many deep learning studies use a large set of meteorological and time-based variables because of the belief that more inputs improve model performance. In practice, a large feature set can introduce redundancy, increa...
Gorde:
| Egile Nagusiak: | , , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
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MDPI AG
2025-12-01
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| Saila: | Energies |
| Gaiak: | |
| Sarrera elektronikoa: | https://www.mdpi.com/1996-1073/18/24/6395 |
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