Comments: Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater

Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater

To maintain human health and purity of drinking water, it is crucial to eliminate harmful chemicals such as nitrophenols and azo dyes, considering their natural presence in the surroundings. In this particular research study, the application of machine learning techniques was employed in order to ma...

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Bibliographic Details
Main Authors:	Khan M.S.J., Sidek L.M., Kumar P., Alkhadher S.A.A., Basri H., Zawawi M.H., El-Shafie A., Ahmed A.N.
Other Authors:	57214778682
Format:	Article
Published:	Elsevier B.V. 2025
Subjects:	Algorithms Azo Compounds Catalysis Coloring Agents Machine Learning Nitrophenols Silver Wastewater Water Pollutants, Chemical Water Purification Wastewater treatment azo dye nitrophenol 4-nitrophenol azo compound coloring agent silver % reductions 4-Nitrophenol Aquatic waste Azo-dyes Catalytic performance Dye reduction Machine-learning ]+ catalyst adaptive moment estimation Article catalysis catalyst electromagnetic radiation electron energy resource learning algorithm long short term memory network machine learning mean absolute error pollutant recurrent neural network time series analysis waste water management wastewater water pollutant algorithm chemistry isolation and purification procedures water management Azo dyes
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Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater

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