[HTML][HTML] Small scale desalination technologies: A comprehensive review

H Kariman, A Shafieian, M Khiadani - Desalination, 2023 - Elsevier
In recent decades, problems related to fresh water has become a very important issue for
humans. Small-scale desalination (SSD) systems, besides large-scale desalination (LSD) …

[HTML][HTML] Machine learning-aided modeling for predicting freshwater production of a membrane desalination system: A long-short-term memory coupled with election …

M Abd Elaziz, ME Zayed, H Abdelfattah… - Alexandria Engineering …, 2024 - Elsevier
Membrane desalination (MD) is an efficient process for desalinating saltwater, combining
the uniqueness of both thermal and separation distillation configurations. In this context, the …

[HTML][HTML] Machine learning toward improving the performance of membrane-based wastewater treatment: A review

P Dansawad, Y Li, Y Li, J Zhang, S You, W Li, S Yi - Advanced Membranes, 2023 - Elsevier
Abstract Machine learning (ML) is a data-driven approach that can be applied to design,
analyze, predict, and optimize a process based on existing data. Recently, ML has found its …

Machine learning modelling of a membrane capacitive deionization (MCDI) system for prediction of long-term system performance and optimization of process control …

Y Zhu, B Lian, Y Wang, C Miller, C Bales, J Fletcher… - Water Research, 2022 - Elsevier
Abstract Membrane Capacitive Deionization (MCDI) is a promising electrochemical
technique for water desalination. Previous studies have confirrmed the effectiveness of …

Enhanced performance of a hybrid adsorption desalination system integrated with solar PV/T collectors: Experimental investigation and machine learning modeling …

ME Zayed, M Ghazy, B Shboul, MR Elkadeem… - Applied Thermal …, 2024 - Elsevier
This study explores the performance augmentation of a solar adsorption desalination system
(SADS) powered by a hybrid solar thermal system with evacuated tubes and photovoltaic …

An evolutionary deep learning soft sensor model based on random forest feature selection technique for penicillin fermentation process

L Hua, C Zhang, W Sun, Y Li, J Xiong, MS Nazir - ISA transactions, 2023 - Elsevier
Accurate and reliable measurement of key biological parameters during penicillin
fermentation is of great significance for improving penicillin production. In this research …

Machine learning-guided underlying decisive factors of high-performance membrane distillation system: Membrane properties, operation conditions and solution …

J Ma, H Xu, A Wang, A Wang, L Gao, M Ding - Separation and Purification …, 2023 - Elsevier
Membrane distillation (MD) is considered as one of the promising membrane technologies
with the potential to effectively produce freshwater from high concentration brines …

Enhancing waste cooking oil biodiesel yield and characteristics through machine learning, response surface methodology, and genetic algorithms for optimal …

A Ahmad, AK Yadav, A Singh - International Journal of Green …, 2024 - Taylor & Francis
The current study seeks to predict and optimize the biodiesel production yield and
physicochemical properties of waste cooking oil. Using Box-Behnken design (BBD), L46 …

Prediction of outlet air characteristics and thermal performance of a symmetrical solar air heater via machine learning to develop a model-based operational control …

M Moghadasi, H Ghadamian, M Moghadasi… - … Science and Pollution …, 2023 - Springer
This study develops reliable and robust machine learning (ML) models to predict the outlet
air temperature and humidity and thermal efficiency of a solar air heater (SAH). Also, the …

Deep learning with improved hybrid neuro-turning for predictive control of flux based on experimental DCMD module design of water desalination system

O Shamet, SI Abba, J Usman, DU Lawal… - Journal of Water …, 2024 - Elsevier
This study explores two scenarios for optimizing the predictive control of flux in water
desalination systems: experimental design of direct contact membrane distillation (DCMD) …