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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:

Explainable machine learning methods for predicting water treatment plant features under varying weather conditions
Mohammed Al Saleem, Fouzi Harrou, Ying Sun
Results in Engineering (2024) Vol. 21, pp. 101930-101930
Open Access | Times Cited: 21

Showing 21 citing articles:

Compressive strength prediction models for concrete containing nano materials and exposed to elevated temperatures
Hany A. Dahish, Ahmed D. Almutairi
Results in Engineering (2025), pp. 103975-103975
Open Access | Times Cited: 2
Global research landscape on coagulation-flocculation for wastewater treatment: A 2000–2023 bibliometric analysis
Mohamed Hizam Mohamed Noor, Norzita Ngadi
Journal of Water Process Engineering (2024) Vol. 64, pp. 105696-105696
Closed Access | Times Cited: 14
Enhancing interpretability of tree-based models for downstream salinity prediction: Decomposing feature importance using the Shapley additive explanation approach
Guang-yao Zhao, Kenji Ohsu, Henry Kasmanhadi Saputra, et al.
Results in Engineering (2024) Vol. 23, pp. 102373-102373
Open Access | Times Cited: 7
Comparison and integration of physical and interpretable AI-driven models for rainfall-runoff simulation
Sara Asadi, Patricia Jimeno‐Sáez, Adrián López-Ballesteros, et al.
Results in Engineering (2024) Vol. 24, pp. 103048-103048
Open Access | Times Cited: 7
Machine learning-driven habitat suitability modeling of Suaeda aegyptiaca for sustainable industrial cultivation in saline regions
Sara Edrisnia, Mohammad Etemadi, Hamid Reza Pourghasemi
Industrial Crops and Products (2025) Vol. 225, pp. 120427-120427
Open Access
Evaluating e-learning readiness using explainable machine learning and key organizational change factors in higher education
Mohamed Zine, Fouzi Harrou, Mohammed Terbeche, et al.
Education and Information Technologies (2025)
Open Access
Predictive Modeling of Co2 and Methane Adsorption in Tight Reservoirs Using Machine Learning Techniques
Mehdi Maleki, Mohammad Rasool Dehghani, Moein Kafi, et al.
(2025)
Closed Access
Optimization of Municipal Wastewater Treatment Plants Management through Digital Twin Modeling
Ku‐Fan Chen, Chih‐Ming Kao
Journal of Environmental Engineering (2025) Vol. 151, Iss. 4
Closed Access
Experimental study and correlation analysis of breakup characteristics of liquid nitrogen jets
Yanling Yang, Kang Cen, Mengxin Li, et al.
Experimental Thermal and Fluid Science (2025), pp. 111443-111443
Closed Access
Evaluating Machine Learning-Based Soft Sensors for Effluent Quality Prediction in Wastewater Treatment Under Variable Weather Conditions
Daniel Voipan, Andreea Elena Voipan, Marian Barbu
Sensors (2025) Vol. 25, Iss. 6, pp. 1692-1692
Open Access
Leveraging Artificial Intelligence Models (GBR, SVR, and GA) for Efficient Chromium Reduction via UV/Trichlorophenol/Sulfite Reaction
Amir H. Mohammadi, Parsa Khakzad, Tayebeh Rasolevandi, et al.
Results in Engineering (2025), pp. 104599-104599
Open Access
Enhancing Defect Detection in Steel Plate Manufacturing with Explainable Machine Learning and SMOTE for Imbalanced Data
Abdelhakim Dorbane, Fouzi Harrou, Ying Sun
Journal of Materials Engineering and Performance (2025)
Closed Access
Enhanced data-driven monitoring of wastewater treatment plants using the Kolmogorov–Smirnov test
K. Ramakrishna Kini, Fouzi Harrou, Muddu Madakyaru, et al.
Environmental Science Water Research & Technology (2024) Vol. 10, Iss. 6, pp. 1464-1480
Open Access | Times Cited: 3
Explainable machine learning for enhancing predictive accuracy of cutting forces in hard turning processes
Abdelhakim Dorbane, Fouzi Harrou, Ying Sun, et al.
The International Journal of Advanced Manufacturing Technology (2024)
Closed Access | Times Cited: 3
Perfluorooctanoic Acids (PFOA) removal using electrochemical oxidation: A machine learning approach
Sally Alnaimat, Osama Mohsen, Haitham Elnakar
Journal of Environmental Management (2024) Vol. 370, pp. 122857-122857
Closed Access | Times Cited: 2
Efficient Computational Investigation on Accurate Daily Soil Temperature Prediction Using Boosting Ensemble Methods Explanation Based on SHAP Importance Analysis
Meysam Alizamir, Mo Wang, Rana Muhammad Adnan Ikram, et al.
Results in Engineering (2024), pp. 103220-103220
Open Access | Times Cited: 2
Enhancing photovoltaic system performance using advanced gradient boosting methods
Fouzi Harrou, Abdelhakim Dorbane, Ying Sun
(2024), pp. 1-6
Closed Access | Times Cited: 1
A fascinating exploration into nitrite accumulation into low concentration reactors using cutting-edge machine learning techniques
Hareef Ahmed Keerio, Sabab Ali Shah, Zouhaib Ali, et al.
Process Biochemistry (2024) Vol. 146, pp. 160-168
Closed Access | Times Cited: 1
Prediction of non-stationary daily streamflow series based on ensemble learning: a case study of the Wei River Basin, China
Wei Ma, Xiao Zhang, Jiancang Xie, et al.
Stochastic Environmental Research and Risk Assessment (2024)
Closed Access | Times Cited: 1
Exploring Antiviral Drugs on Monolayer Black Phosphorene: Atomistic Theory and Explainable Machine Learning-Assisted Platform
S. Laref, Fouzi Harrou, Ying Sun, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 9, pp. 4897-4897
Open Access
Gated Recurrent Unit with Self Attention Mechanism for Optimizing Wastewater Treatment Process
L. Zhang
(2024) Vol. 11, pp. 01-04
Closed Access
Machine learning application in municipal wastewater treatment to enhance the performance of a sequencing batch reactor wastewater treatment plant
Hagar H. Hassan
Environmental Science Advances (2024) Vol. 4, Iss. 1, pp. 125-132
Open Access
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