Incremental transfer learning based on temporal-frequency convolution interaction for multi-task prediction of wind speed and wind power
This paper introduces an incremental transfer learning approach based on temporal-frequency convolution interaction for multi-task prediction of wind speed and power in newly-built wind farms with insufficient historical data. The method integrates a temporal-frequency convolutional interactive neural network into a parallel framework with circular convolution and gated recurrent units, achieving significant reduction in prediction errors compared to classical LSTM algorithms.
Jul 5, 2025
