João Vitor Rios Fuck, Maria Alice Prado Cechinel, Juliana Neves, Rodrigo Campos de Andrade, Ricardo Tristão, Nicolas Spogis, Humberto Gracher Riella, Cíntia Soares, Natan Padoin
Wastewater Treatment Plants (WWTPs) present complex biochemical processes of high variability and difficult prediction. This study presents an innovative approach using Machine Learning (ML) models to predict wastewater quality parameters. In particular, the models are applied to datasets from both a simulated wastewater treatment plant (WWTP), using DHI WEST software (WEST WWTP), and a real-world WWTP database from Santa Catarina Brewery AMBEV, located in Lages/SC - Brazil (AMBEV WWTP). A distinctive aspect is the evaluation of predictive performance in continuous data scenarios and the impact of changes in WWTP operations on predictive model performance, including changes in plant layout...
February 19, 2024: Chemosphere