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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Machine learning-based real-time prediction of micropollutant behaviour in forward osmosis membrane (waste)water treatment
Nguyen Duc Viet, Am Jang
Journal of Cleaner Production (2023) Vol. 389, pp. 136023-136023
Closed Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches
Ali Aldrees, Majid Khan, Abubakr Taha Bakheit Taha, et al.
Journal of Water Process Engineering (2024) Vol. 58, pp. 104789-104789
Closed Access | Times Cited: 60
Revolutionizing wastewater treatment toward circular economy and carbon neutrality goals: Pioneering sustainable and efficient solutions for automation and advanced process control with smart and cutting-edge technologies
Stefano Cairone, Shadi W. Hasan, Kwang‐Ho Choo, et al.
Journal of Water Process Engineering (2024) Vol. 63, pp. 105486-105486
Open Access | Times Cited: 17
Machine learning: Next promising trend for microplastics study
Jiming Su, Fupeng Zhang, Chuanxiu Yu, et al.
Journal of Environmental Management (2023) Vol. 344, pp. 118756-118756
Closed Access | Times Cited: 32
Integrating artificial intelligence modeling and membrane technologies for advanced wastewater treatment: Research progress and future perspectives
Stefano Cairone, Shadi W. Hasan, Kwang‐Ho Choo, et al.
The Science of The Total Environment (2024) Vol. 944, pp. 173999-173999
Open Access | Times Cited: 13
Modeling and multi-objective optimization of forward osmosis process
Tina Kegl, Jasmina Korenak, Hermina Bukšek, et al.
Desalination (2024) Vol. 580, pp. 117550-117550
Open Access | Times Cited: 10
Machine learning for the advancement of membrane science and technology: A critical review
Gergő Ignácz, Lana Bader, Aron K. Beke, et al.
Journal of Membrane Science (2024) Vol. 713, pp. 123256-123256
Open Access | Times Cited: 10
Unit Operation and Process Modeling with Physics-Informed Machine Learning
Haochen Li, David Spelman, John J. Sansalone
Journal of Environmental Engineering (2024) Vol. 150, Iss. 4
Open Access | Times Cited: 8
Optimizing Membrane Bioreactor Performance in Wastewater Treatment Using Machine Learning and Meta-Heuristic Techniques
Usman M. Ismail, Khalid Bani‐Melhem, Muhammad Faizan Khan, et al.
Results in Engineering (2025), pp. 104626-104626
Open Access | Times Cited: 1
Optimization and prediction of lead removal from aqueous solution using FO–MD hybrid process: Statistical and artificial intelligence analysis
Ali Boubakri, Sarra Elgharbi, Imen Dhaouadi, et al.
Journal of Environmental Management (2023) Vol. 337, pp. 117731-117731
Closed Access | Times Cited: 19
Optimized prediction modeling of micropollutant removal efficiency in forward osmosis membrane systems using explainable machine learning algorithms
Ali Aldrees, Muhammad Faisal Javed, Majid Khan, et al.
Journal of Water Process Engineering (2024) Vol. 66, pp. 105937-105937
Closed Access | Times Cited: 4
Enhancing Hydrogen Sulfide Control in Urban Sewer Systems Using Machine Learning Models: Development of a New Predictive Simulation Approach by using Boosting Algorithm
Nguyen Duc Viet, Miran Seo, Yue Chen, et al.
Journal of Hazardous Materials (2025) Vol. 491, pp. 137906-137906
Closed Access
Predicting biochemical oxygen demand in wastewater treatment plant using advance extreme learning machine optimized by Bat algorithm
Hayat Mekaoussi, Salim Heddam, Nouri Bouslimanni, et al.
Heliyon (2023) Vol. 9, Iss. 11, pp. e21351-e21351
Open Access | Times Cited: 10
A Survey of Machine and Deep Learning Applications in the Assessment of Water Quality
Mourade Azrour, Souhayla Dargaoui, Jamal Mabrouki, et al.
World sustainability series (2024), pp. 471-483
Closed Access | Times Cited: 3
Navigating the difference of riverine microplastic movement footprint into the sea: Particle properties influence
Yichuan Zeng, Hua Wang, Dongfang Liang, et al.
Journal of Hazardous Materials (2024) Vol. 476, pp. 134888-134888
Closed Access | Times Cited: 3
Artificial Intelligence Applications in Forward Osmosis for Water Treatment: Recent Developments and Research Directions
Saleh O. Alaswad, Eydhah Almatrafi
Desalination and Water Treatment (2024) Vol. 319, pp. 100551-100551
Open Access | Times Cited: 3
Utilising Artificial Intelligence to Predict Membrane Behaviour in Water Purification and Desalination
Reza Shahouni, Mohsen Abbasi, Mahdieh Dibaj, et al.
Water (2024) Vol. 16, Iss. 20, pp. 2940-2940
Open Access | Times Cited: 3
Modeling of osmotically-driven membrane processes: An overview
Mohammad Aquib Wakeel Khan, Mohd Muzammil Zubair, Haleema Saleem, et al.
Desalination (2023) Vol. 573, pp. 117183-117183
Closed Access | Times Cited: 8
Applications of artificial intelligence for membrane separation: A review
Mehryar Jafari, Christina Tzirtzipi, Bernardo Castro‐Dominguez
Journal of Water Process Engineering (2024) Vol. 68, pp. 106532-106532
Open Access | Times Cited: 2
Artificial intelligence optimization and controllable slow-release iron sulfide realizes efficient separation of copper and arsenic in strongly acidic wastewater
Xingfei Zhang, Chenglong Lu, Jia Tian, et al.
Journal of Environmental Sciences (2023) Vol. 139, pp. 293-307
Closed Access | Times Cited: 5
Identification of surface water quality pollution areas and pollution sources based on spatial clustering and random forest in Henan, China
Huaibin Wei, Haojie Qiu, Jing Liu, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Evaluating nano-metal oxide mixed matrix membranes for whey protein separation using hybrid intelligent optimization learning
Lukka Thuyavan Yogarathinam, Jamilu Usman, Sani I. Abba, et al.
Process Safety and Environmental Protection (2024) Vol. 205, pp. 388-400
Closed Access | Times Cited: 1
Predicting micropollutant removal through nanopore-sized membranes using several machine-learning approaches based on feature engineering
Lukka Thuyavan Yogarathinam, Sani I. Abba, Jamilu Usman, et al.
RSC Advances (2024) Vol. 14, Iss. 27, pp. 19331-19348
Open Access | Times Cited: 1
Accurate Prediction of Reverse Solute Flux in Forward Osmosis Systems Using Comparative Machine Learning Models
Ali Boubakri, Sarra Elgharbi, S. Bouguecha, et al.
Arabian Journal for Science and Engineering (2024)
Closed Access | Times Cited: 1
Predicting and Optimizing Forward Osmosis Membrane Operation Using Machine Learning
Mita Nurhayati, Kwanho Jeong, Haeryong Lee, et al.
(2024)
Closed Access | Times Cited: 1
Predicting and optimizing forward osmosis membrane operation using machine learning
Mita Nurhayati, Kwanho Jeong, H Lee, et al.
Desalination (2024), pp. 118154-118154
Closed Access | Times Cited: 1
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