Short-term wind power forecasting through stacked and bi directional LSTM techniques
Mehmood Ali Khan,
Iftikhar Ahmed Khan,
Sajid Shah
et al.
Abstract:Background
Computational intelligence (CI) based prediction models increase the efficient and effective utilization of resources for wind prediction. However, the traditional recurrent neural networks (RNN) are difficult to train on data having long-term temporal dependencies, thus susceptible to an inherent problem of vanishing gradient. This work proposed a method based on an advanced version of RNN known as long short-term memory (LSTM) architecture, which updates recurrent weights to overcom… Show more
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