Fig. 3
From: Short-term water demand forecasting using hybrid supervised and unsupervised machine learning model
SARIMA model algorithm. This figure shows the algorithm used to develop SARIMA forecasting models. Processed data is fed to the model where the model order parameters are identified by plotting the Autocorrelation Factor (ACF) and the Partial Autocorrelation Factor (PACF). After reaching a satisfying performance, the time ahead input data is read to predict the response (i.e. the water demand)