Bio-inspired MXene membranes for enhanced separation and anti-fouling in oil-in-water emulsions: SHAP explainability ML

Bio-inspired MXene membranes for enhanced separation and anti-fouling in oil-in-water emulsions: SHAP explainability ML

Optimizing membrane performance for efficient water treatment is crucial for sustainable development and environmental protection, aligning with UN SDGs. This study involves experimental design, statistical reliability of small data, and explainable machine learning (ML) using SHAP (Shapley Additive...

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Bibliographic Details
Main Authors: Nadeem Baig, Sani I. Abba, Jamil Usman, Ibrahim Muhammad, Ismail Abdulazeez, A.G. Usman, Isam H. Aljundi
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Cleaner Water
Subjects:
environmental sustainability
clean water access
machine learning
MXene
reliability analysis
SHAP
Online Access:http://www.sciencedirect.com/science/article/pii/S2950263224000395
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http://www.sciencedirect.com/science/article/pii/S2950263224000395

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