Optimizing coagulant dosage using deep learning models with large-scale data.

Water treatment plants are facing challenges that necessitate transition to automated processes using advanced technologies. This study introduces a novel approach to optimize coagulant dosage in water treatment processes by employing a deep learning model. The study utilized minute-by-minute data monitored in real time over a span of five years, marking the first attempt in drinking water process modeling to leverage such a comprehensive dataset.