Modeling and evaluation of the permeate volume in membrane desalination processes using machine-learning techniques-Reference-Cited by-同舟云学术

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Modeling and evaluation of the permeate volume in membrane desalination processes using machine-learning techniques

Published:2024-06 Issue: Volume:11 Page:100154
ISSN:2772-5081
Container-title:Digital Chemical Engineering
language:en
Short-container-title:Digital Chemical Engineering

Author:

S Vinod Kumar,S Mukil,P Naveen,B Senthil Rathi

Publisher

Elsevier BV

Reference35 articles.

1. Current advances in membrane technologies for saline wastewater treatment: a comprehensive review;Ahmad;Desalination,2021

2. An unsupervised stochastic machine learning approach for well log outlier identification;Akkurt,2022

3. A comprehensive review on membrane fouling: mathematical modelling, prediction, diagnosis, and mitigation;AlSawaftah;Water (Basel),2021

4. Unequal effects of disruptive events;Aquino;Sociol. Compass,2022

5. Support vector regression;Awad,2015

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep learning with improved hybrid neuro-turning for predictive control of flux based on experimental DCMD module design of water desalination system;Journal of Water Process Engineering;2024-08

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