… wind speed forecasting results since wind speed series contain complex fluctuations. In
this paper, a novel wind speed forecasting … ) and long short-term memory neural network (LSTM), …

… forecasting model based on Long Short-Term Memory (LSTM) network and BP neural network
… When calculating the complexity of time series, the influence of changing parameters on …

… long short-term memory neural network (LSTM), the adaptive neuro-fuzzy system (ANFIS),
echo state network … has the same trend for two consecutive days, changing only the amplitude …

… The combination of adaptive differential evolution (SADE) and sines and cosine selection …
Short-term wind speed prediction based on LMD and improved FA optimized combined kernel …

… wind speed forecasting is proposed in this study by combining a convolutional neural network
and a long short-term memory neural network… fth meteorological factor changing with time …

… prediction model based on long short-term memory and a deep neural network developed to
forecast the wind speed … are training sequences with changing values in one time step. That …

… in wind speed forecasting field. Recently, some deep learning methods, such as the DBN
(Deep Belief Network) and LSTM (Long Short Term Memory), … , GWO evolutionary optimization, …

… In this paper, a multi-variable long short-term memory network … , and the wind evolution,
physical methods perform poorly in … BP neural network prediction method, and long-term and …

… The long short term memory neural network, a deep learning … to predict the low-frequency
wind speed sub-layers. The Elman … prediction models simulate the wind speed changing by …

… forecasting performance. In this paper, a new hybrid WSF model is developed based on long
short-term memory (LSTM) network … intelligence-based evolutionary computation method …