Comparative analysis of feed-forward neural network and second-order polynomial regression in textile wastewater treatment efficiency

Comparative analysis of feed-forward neural network and second-order polynomial regression in textile wastewater treatment efficiency

This study refines a single-layer Feed-Forward Neural Network (FFNN) for the treatment of textile dye wastewater, concentrating on percentage decolorization (%DEC) and percentage chemical oxygen demand (%COD) reduction. The optimized neural network configuration comprises four input and one output n...

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Bibliographic Details
Main Authors:	Ali S. Alkorbi, Muhammad Tanveer, Humayoun Shahid, Muhammad Bilal Qadir, Fayyaz Ahmad, Zubair Khaliq, Mohammed Jalalah, Muhammad Irfan, Hassan Algadi, Farid A. Harraz
Format:	Article
Language:	English
Published:	AIMS Press 2024-03-01
Series:	AIMS Mathematics
Subjects:	feed-forward neural network machine learning multi-objective optimization treatment of textile wastewater decolorization chemical oxygen demand sustainable environment
Online Access:	https://www.aimspress.com/article/doi/10.3934/math.2024536?viewType=HTML

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