Machine learning-aided prediction of COD removal in the electrocoagulation process using a super learner model

Machine learning-aided prediction of COD removal in the electrocoagulation process using a super learner model

<p dir="ltr">A new predictive machine learning stacking model was developed to examine chemical oxygen demand (COD) removal efficiency in electrocoagulation. The model used a comprehensive dataset consisting of 379 points containing no missing data collected from different studies in...

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Bibliographic Details
Main Author: Mhd Taisir Albaba (20601071) (author)
Other Authors: Mohammed Talhami (17302756) (author), Abdullah Omar (6468326) (author), Sumith Varghese (21797462) (author), Rayane Akoumeh (18560659) (author), Mohamed Arselene Ayari (16869978) (author), Probir Das (14151690) (author), Ali Altaee (4902520) (author), Maryam AL-Ejji (17337922) (author), Alaa H. Hawari (14151681) (author)
Published: 2025
Subjects:
Engineering
Chemical engineering
Environmental engineering
Information and computing sciences
Machine learning
Electrocoagulation
COD removal
Machine Learning
Water treatment
Super-learner model
Chemical oxygen demand
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