# ARIMA-ANN Hybrid Model for Timeseries forecasting

I want to implement a hybrid ARIMA-ANN model but i dont know if the procedure i followed is the right one. Below i will describe you the steps i made.

1. Fitting Arima model into my dataset and found the residuals from entire data.

2. Create X_train, y_train from training set of residuals and X_val, y_val from testing set of residuals.

3. Create Neural Network (with keras) and fit my data

4. Sum my predictions from Arima model with the prediction from NN model

Is this the right way to implement the hybrid model or i should make same changes? The results by this model are worse than ARIMA, ANN models separately

References to this hybrid model can be found here: https://www.sciencedirect.com/science/article/pii/S0925231201007020

All help is appreciated.

I would split my data into a $train$, $val_1$ set, and $val_2$ set.
Fit the ARIMA model to $train$ + $val_1$ and the calculate your residuals, the train the NNet on the residuals from $train$ and test on the residuals from $val_1$.
Once you are satisfied with the Neural Net chosen, fit the hybrid ARIMA-ANN model on $train$ + $val_1$ and test on $val_2$.