Comparative analysis and application of soft sensor models in domestic wastewater treatment for advancing sustainability.

This study focuses on the development and evaluation of soft sensor models for predicting NH-N values in a wastewater treatment process. The study compares the performance of linear regression (LR), neural networks (NN) and random forest regression (RFR) models. The proposed methodology involves optimizing the sequencing batch reactor process using artificial intelligence and an automatic control system.