Incorporating causality in energy consumption forecasting using deep neural networks

HIGHLIGHTS

• who: Kshitij Sharma from the Department of Computer Science, Norwegian University of Science and Technology, Trondheim, #323, Bay Campus, Fabian Bay, Swansea , EN, Wales, UK have published the article: Incorporating causality in energy consumption forecasting using deep neural networks, in the Journal: (JOURNAL)
• what: The main reason for Bi-LSTM outperforming the simple LSTM can be attributed to the fact that by using two hidden states for each time step, the information from the past and the future is preserved, which in turn provides a better approximation of the time series and encodes the contexts . . .
  

   

  

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