💻 computer science
Hybrid LSTM-Transformer-ACO deep learning models for time series forecasting of solar power
This study proposes a novel hybrid deep learning framework combining LSTM, Transformer, and Ant Colony Optimization (ACO) that, when optimized with Nadam, achieves superior accuracy and computational efficiency for real-time solar power and electrical load forecasting compared to standalone and competing hybrid models.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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