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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:

Environmental assessment based surface water quality prediction using hyper-parameter optimized machine learning models based on consistent big data
Muhammad Izhar Shah, Muhammad Faisal Javed, Abdulaziz Alqahtani, et al.
Process Safety and Environmental Protection (2021) Vol. 151, pp. 324-340
Closed Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Indices and models of surface water quality assessment: Review and perspectives
Tao Yan, Shui‐Long Shen, Annan Zhou
Environmental Pollution (2022) Vol. 308, pp. 119611-119611
Closed Access | Times Cited: 113
Optimization of water quality index models using machine learning approaches
Fei Ding, Wenjie Zhang, Shaohua Cao, et al.
Water Research (2023) Vol. 243, pp. 120337-120337
Closed Access | Times Cited: 82
Novel Groundwater Quality Index (GWQI) model: A Reliable Approach for the Assessment of Groundwater
Abdul Majed Sajib, Apoorva Bamal, Mir Talas Mahammad Diganta, et al.
Results in Engineering (2025), pp. 104265-104265
Open Access | Times Cited: 2
Prediction model of drinking water source quality with potential industrial-agricultural pollution based on CNN-GRU-Attention
Peng Mei, Meng Li, Qian Zhang, et al.
Journal of Hydrology (2022) Vol. 610, pp. 127934-127934
Closed Access | Times Cited: 62
Machine learning modeling integrating experimental analysis for predicting the properties of sugarcane bagasse ash concrete
Muhammad Izhar Shah, Muhammad Faisal Javed, Fahid Aslam, et al.
Construction and Building Materials (2021) Vol. 314, pp. 125634-125634
Closed Access | Times Cited: 58
Comparative Assessment of Individual and Ensemble Machine Learning Models for Efficient Analysis of River Water Quality
Abdulaziz Alqahtani, Muhammad Izhar Shah, Ali Aldrees, et al.
Sustainability (2022) Vol. 14, Iss. 3, pp. 1183-1183
Open Access | Times Cited: 56
Prediction of long-term water quality using machine learning enhanced by Bayesian optimisation
Tao Yan, Annan Zhou, Shui‐Long Shen
Environmental Pollution (2022) Vol. 318, pp. 120870-120870
Closed Access | Times Cited: 56
Modeling the organic matter of water using the decision tree coupled with bootstrap aggregated and least-squares boosting
Hichem Tahraoui, Abdeltif Amrane, Abd-Elmouneïm Belhadj, et al.
Environmental Technology & Innovation (2022) Vol. 27, pp. 102419-102419
Open Access | Times Cited: 52
Modeling Multistep Ahead Dissolved Oxygen Concentration Using Improved Support Vector Machines by a Hybrid Metaheuristic Algorithm
Rana Muhammad Adnan, Hongliang Dai, Reham R. Mostafa, et al.
Sustainability (2022) Vol. 14, Iss. 6, pp. 3470-3470
Open Access | Times Cited: 41
A multi-model data fusion methodology for reservoir water quality based on machine learning algorithms and bayesian maximum entropy
Mohammad Zamani, Mohammad Reza Nikoo, Fereshteh Niknazar, et al.
Journal of Cleaner Production (2023) Vol. 416, pp. 137885-137885
Closed Access | Times Cited: 36
Water quality prediction of copper-molybdenum mining-beneficiation wastewater based on the PSO-SVR model
Xiaohua Fu, Qingxing Zheng, Guomin Jiang, et al.
Frontiers of Environmental Science & Engineering (2023) Vol. 17, Iss. 8
Closed Access | Times Cited: 26
Forecasting biochemical oxygen demand (BOD) in River Ganga: a case study employing supervised machine learning and ANN techniques
Rohan Mishra, Rupanjali Singh, C. B. Majumder
Sustainable Water Resources Management (2025) Vol. 11, Iss. 1
Closed Access | Times Cited: 1
Predictive Modeling Approach for Surface Water Quality: Development and Comparison of Machine Learning Models
Muhammad Izhar Shah, Wesam Salah Alaloul, Abdulaziz Alqahtani, et al.
Sustainability (2021) Vol. 13, Iss. 14, pp. 7515-7515
Open Access | Times Cited: 53
Introducing a Novel Hybrid Machine Learning Model and Developing its Performance in Estimating Water Quality Parameters
Mojtaba Kadkhodazadeh, Saeed Farzin
Water Resources Management (2022) Vol. 36, Iss. 10, pp. 3901-3927
Closed Access | Times Cited: 23
Application of hybrid machine learning models and data pre-processing to predict water level of watersheds: Recent trends and future perspective
Sarah Jasim Mohammed, Salah L. Zubaidi, Sandra Ortega‐Martorell, et al.
Cogent Engineering (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 22
A Review of Hybrid Soft Computing and Data Pre-Processing Techniques to Forecast Freshwater Quality’s Parameters: Current Trends and Future Directions
Zahraa S. Khudhair, Salah L. Zubaidi, Sandra Ortega‐Martorell, et al.
Environments (2022) Vol. 9, Iss. 7, pp. 85-85
Open Access | Times Cited: 21
Hybridization of long short-term memory with Sparrow Search Optimization model for water quality index prediction
Vince Paul, Ramesh Babu D R, P. Sreeja, et al.
Chemosphere (2022) Vol. 307, pp. 135762-135762
Closed Access | Times Cited: 20
Bidirectional Long Short-Term Memory (BILSTM) - Support Vector Machine: A new machine learning model for predicting water quality parameters
Zahra Jamshidzadeh, Mohammad Ehteram, Hanieh Shabanian
Ain Shams Engineering Journal (2023) Vol. 15, Iss. 3, pp. 102510-102510
Open Access | Times Cited: 12
Particle swarm and grey wolf optimization: enhancing groundwater quality models through artificial neural networks
Soheil Sahour, Matin Khanbeyki, Vahid Gholami, et al.
Stochastic Environmental Research and Risk Assessment (2023) Vol. 38, Iss. 3, pp. 993-1007
Closed Access | Times Cited: 12
Recent Advances in Surface Water Quality Prediction Using Artificial Intelligence Models
Qingqing Zhang, Xue‐yi You
Water Resources Management (2023) Vol. 38, Iss. 1, pp. 235-250
Closed Access | Times Cited: 12
Improving Forecasting Accuracy of Multi-Scale Groundwater Level Fluctuations Using a Heterogeneous Ensemble of Machine Learning Algorithms
Dilip Kumar Roy, Tasnia Hossain Munmun, Chitra Rani Paul, et al.
Water (2023) Vol. 15, Iss. 20, pp. 3624-3624
Open Access | Times Cited: 11
Machine Learning-Based Prediction of Unconfined Compressive Strength of Sands Treated by Microbially-Induced Calcite Precipitation (MICP): A Gradient Boosting Approach and Correlation Analysis
Saeed Talamkhani
Advances in Civil Engineering (2023) Vol. 2023, pp. 1-20
Open Access | Times Cited: 11
A combination of large eddy simulation and physics-informed machine learning to predict pore-scale flow behaviours in fibrous porous media: A case study of transient flow passing through a surgical mask
Mehrdad Mesgarpour, Rabeeah Habib, Mostafa Safdari Shadloo, et al.
Engineering Analysis with Boundary Elements (2023) Vol. 149, pp. 52-70
Open Access | Times Cited: 10
Prediction of surface runoff quality and quantity using an integrated model and machine learning under climate change conditions
Pourya Alipour Atmianlu, Naser Mehrdadi, Majid Shafiepour Motlagh, et al.
Stochastic Environmental Research and Risk Assessment (2025)
Closed Access
Unlocking IoT and Machine Learning’s Potential for Water Quality Assessment: An Extensive Analysis and Future Directions
Shivendra Dubey, Sakshi Dubey, Kapil Raghuwanshi
Water Conservation Science and Engineering (2025) Vol. 10, Iss. 1
Closed Access
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