共 18 条
[1]
Hybrid forecasting model based on long short term memory network and deep learning neural network for wind signal.[J].Yong Qin;Kun Li;Zhanhao Liang;Brendan Lee;Fuyong Zhang;Yongcheng Gu;Lei Zhang;Fengzhi Wu;Dragan Rodriguez.Applied Energy.2019,
[2]
An ensemble long short-term memory neural network for hourly PM 2.5 concentration forecasting.[J].Yun Bai;Bo Zeng;Chuan Li;Jin Zhang.Chemosphere.2019,
[3]
Multi-step ahead wind speed prediction based on optimal feature extraction; long short term memory neural network and error correction strategy.[J].Jujie Wang;Yaning Li.Applied Energy.2018,
[4]
LSTM-EFG for wind power forecasting based on sequential correlation features.[J].Ruiguo Yu;Jie Gao;Mei Yu;Wenhuan Lu;Tianyi Xu;Mankun Zhao;Jie Zhang;Ruixuan Zhang;Zhuo Zhang.Future Generation Computer Systems.2018,
[5]
Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition; singular spectrum analysis; LSTM network and ELM.[J].Hui Liu;Xiwei Mi;Yanfei Li.Energy Conversion and Management.2018,
[6]
Wind speed forecasting method based on deep learning strategy using empirical wavelet transform; long short term memory neural network and Elman neural network.[J].Hui Liu;Xi-wei Mi;Yan-fei Li.Energy Conversion and Management.2018,
[7]
[8]
[9]
[10]