Leveraging machine learning to predict DBPs formation and identify its critical determinants in drinking water treatment

Key Points

• Disinfection byproducts formation is predicted using machine learning techniques, enhancing water treatment efficiency.
• Key factors influencing disinfection byproducts include specific water characteristics and treatment processes.
• This analysis employs predictive modeling to assess drinking water treatment processes and their outcomes.
• Improving predictive capabilities supports better water quality and public health outcomes in the long term.