A selective memory attention mechanism for chaotic wind speed time series prediction with auxiliary variable
This paper proposes a novel selective memory attention mechanism to enhance wind speed prediction accuracy by leveraging auxiliary variables. The method introduces an adaptive frequency-domain selection attention weight operator to parse effective information from different frequency intervals, significantly reducing prediction errors compared to classical LSTM algorithms.
Jul 5, 2025
