Disclaimer: Not from math background
I want to use neural networks for forecasting a time series data. I am reading/watching basics about ACF and PACF. While reading about those functions I came to understand that PACF is an important function to find different time series models for example AR(1), AR(2) etc which tells us which lagged time series is important for forecasting.
In the above PACF image time series lagged at 1,2,12,24 are more prominent and above confidence level. Can we use these time series lagged data Y(t-1),Y(t-2),Y(t-12), and Y(t-24) as the feature vectors for neural network for training to forecast Y(t+n)?