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Multi-step wind speed forecasting based on multi-task learning using mixed granularity collaborative network
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DOI：10.1016/j.energy.2026.140173.png)
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Abstract
En 中文
• MGCNet is proposed for multi-step wind speed forecasting. • Parallel channels separately capture high-frequency fluctuations and trends. • Granularity fusion enables information interaction between time scales. • MGCNet demonstrates superior robustness in high-volatility challenging periods.
Journal
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9.4
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4.3W
Citations:
20.2W
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Cited Papers
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