Forecasting wind speed using empirical mode decomposition and Elman neural network

@article{Wang2014ForecastingWS,
  title={Forecasting wind speed using empirical mode decomposition and Elman neural network},
  author={Jujie Wang and Wenyu Zhang and Yaning Li and Jianzhou Wang and Zhangli Dang},
  journal={Appl. Soft Comput.},
  year={2014},
  volume={23},
  pages={452-459}
}
Because of the chaotic nature and intrinsic complexity of wind speed, it is difficult to describe the moving tendency of wind speed and accurately forecast it. In our study, a novel EMD–ENN approach, a hybrid of empirical mode decomposition (EMD) and Elman neural network (ENN), is proposed to forecast wind speed. First, the original wind speed datasets are decomposed into a collection of intrinsic mode functions (IMFs) and a residue by EMD, yielding relatively stationary sub-series that can be… CONTINUE READING

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