Recurrent Neural Networks for Time Series Forecasting: Current status and future directions

Hewamalage, Hansika; Bergmeir, Christoph; Bandara, Kasun

doi:10.1016/j.ijforecast.2020.06.008

Recurrent Neural Networks for Time Series Forecasting: Current status and future directions

Recurrent Neural Networks (RNNs) have become competitive forecasting methods, as most notably shown in the winning method of the recent M4 competition. However, established statistical models such as exponential smoothing (ETS) and the autoregressive integrated moving average (ARIMA) gain their p…