A hybrid model for multi-step wind speed forecasting based on secondary decomposition, deep learning, and error correction algorithms

A new hybrid model was proposed to improve wind speed forecasting performance, consisting of data pre-processing, model forecasting, and error correction (EC), and test results show that the forecasting performance of the proposed model is better than the other 13 models in three actual datasets.