Machine learning algorithms to predict the catalytic reduction performance of eco-toxic nitrophenols and azo dyes contaminants (Invited Article)

Machine learning algorithms to predict the catalytic reduction performance of eco-toxic nitrophenols and azo dyes contaminants (Invited Article)

Removing hazardous substances like azo dyes and nitrophenols from drinking water is essential for maintaining human health since these substances occur naturally in the environment. This research study used machine learning techniques to estimate the catalytic reduction performance of environmentall...

Full description

Bibliographic Details
Main Authors: V.E. Sathishkumar, A.G. Ramu, Jaehyuk Cho
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:Alexandria Engineering Journal
Subjects:
Machine learning
Wastewater treatment
Dye reduction
Agricultural waste
PdO-NiO
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016823002806

Internet

http://www.sciencedirect.com/science/article/pii/S1110016823002806

Similar Items