Integrating gated recurrent unit in graph neural network to improve infectious disease prediction: an attempt

HIGHLIGHTS

• What: The aim of this study is to try to introduce a GRU (Gated Recurrent Unit) layer in the graph neural_network to enable the network to better capture and learn the relationship of each single time node within a sequence and the correlation between individual time series. The aim here is to make the input to the ARIMA model a stationary time series. The prediction results of each prediction method in the experiment are not satisfactory in the European dataset, which may be caused by the inadequacy of the type of data collected and the insufficient amount . . .
  

   

  

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