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Application of Machine Learning (ML) and Artificial Intelligence (AI)-Based Tools for Modelling and Enhancing Sustainable Optimization of the Classical/Photo-Fenton Processes for the Landfill Leachate Treatment
This study presents a machine learning (ML)/artificial intelligence (AI)-based perspective to reliably predict and enhance the treatment efficiency of landfill leachate by classical-Fenton (c-Fenton) and photo-Fenton (p-Fenton) processes. This experiment also sought to lower treatment costs by evaluating the impact of using different numbers of UV-c (254 nm) lamps during p-Fenton processes, as well as to develop a sustainable process design for landfill leachate. In the modeling stage, thedoi:10.3390/su141811261 fatcat:52nmpw4pgzanziyelgarfkiedu