Short?term wind speed multistep combined forecasting model based on two?stage decomposition and LSTM

In order to better extract and study the characteristics of wind speed in time-domain frequency-domain, so as solve randomness frequency-domain complexity problems signal, a combined short-term prediction model (WD-VMD-DLSTM-AT), which is based on two-stage decomposition (WD + VMD), double long-short-term memory network (DLSTM) attention mechanism (AT), proposed; this basis, multi-input multiple output (MIMO) codec (MMED-AT) proposed for step forecast. Through experimental comparison analysis, forecasting has smallest statistical error best accuracy; MMED-AT models can obviously eliminate cumulative recursive multistep further improve stability prediction.