Machine learning-based prediction of effluent total suspended solids in a wastewater treatment plant using different feature selection approaches: A comparative study-Reference-Cited by-同舟云学术

Machine learning-based prediction of effluent total suspended solids in a wastewater treatment plant using different feature selection approaches: A comparative study

Published:2024-04 Issue: Volume:246 Page:118146
ISSN:0013-9351
Container-title:Environmental Research
language:en
Short-container-title:Environmental Research

Author:

Gholizadeh Mahdi,Saeedi Reza,Bagheri Amin,Paeezi Mohammad

Funder

Shahid Beheshti University of Medical Sciences

Publisher

Elsevier BV

Reference20 articles.

1. The'K'in K-fold Cross Validation;Anguita,2012

2. Simulation of the biochemical and chemical oxygen demand and total suspended solids in wastewater treatment plants: data-mining approach;Asami;J. Clean. Prod.,2021

3. The Effect of Data Preprocessing on the Performance of Artificial Neural Networks Techniques for Classification Problems;Atomi,2012

4. Comparative study on total nitrogen prediction in wastewater treatment plant and effect of various feature selection methods on machine learning algorithms performance;Bagherzadeh;J. Water Proc. Eng.,2021

5. Understanding the influence of suspended solids on water quality and aquatic biota;Bilotta;Water Res.,2008

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