Abstract:Accurate estimation of wind speed is essential for many meteorological applications. A novel shortterm wind speed prediction method of the BLSTMTRA model is proposed by combining the Transformer model and LSTM model. Six stations along the southern coast of the Shandong Peninsula are selected as the research area. After comparing and analyzing the 6 h prediction results of the 2018 ECMWF model, the following conclusions are drawn: The BLSTMTRA multistep prediction model can reduce the error of wind speed prediction. Compared with the ECMWF prediction model results, the RMSE and MAE of BLSTMTRA are decreased by 58.9% and 63.2% on average. The analysis of wind speed error and wind statistical process shows that the BLSTMTRA model has a certain antiinterference ability and can capture the sensitive information of shortterm wind, etc., which is obviously better than the ECWMF model and traditional LSTM model for wind prediction.