Fig. 5
From: Short-term water demand forecasting using hybrid supervised and unsupervised machine learning model
a SOM model algorithm. This figure shows the algorithm used to develop SARIMA forecasting models. Processed target data is fed to the model where the model is trained, tested, and validated. After reaching a satisfying performance, the time ahead input data is read to predict the response (i.e. the cluster number). b RT model algorithm. This figure shows the algorithm used to develop RT forecasting models. Processed target data is fed to the model where the model is trained, tested, and validated. After reaching a satisfying performance, the time ahead input data is read to predict the response (i.e. the water demand)