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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 methods for imbalanced data set for prediction of faecal contamination in beach waters
M Bourel, Ángel M. Segura, Carolina Crisci, et al.
Water Research (2021) Vol. 202, pp. 117450-117450
Closed Access | Times Cited: 53

Showing 1-25 of 53 citing articles:

Machine learning in natural and engineered water systems
Ruixing Huang, Chengxue Ma, Jun Ma, et al.
Water Research (2021) Vol. 205, pp. 117666-117666
Closed Access | Times Cited: 203
Prediction modelling framework comparative analysis of dissolved oxygen concentration variations using support vector regression coupled with multiple feature engineering and optimization methods: A case study in China
Xizhi Nong, Laifei Cheng, Lihua Chen, et al.
Ecological Indicators (2023) Vol. 146, pp. 109845-109845
Open Access | Times Cited: 61
Machine learning facilitates connections between soil thermal conductivity, soil water content, and soil matric potential
Xiangwei Wang, Yanchen Gao, Jiagui Hou, et al.
Journal of Hydrology (2024) Vol. 633, pp. 130950-130950
Closed Access | Times Cited: 9
Water Quality Prediction of Small-Micro Water Body Based on the Intelligent-Algorithm-Optimized Support Vector Machine Regression Method and Unmanned Aerial Vehicles Multispectral Data
Ke Yao, Yujie Chen, Yucheng Li, et al.
Sustainability (2024) Vol. 16, Iss. 2, pp. 559-559
Open Access | Times Cited: 8
Causality Analysis and Prediction of Riverine Algal Blooms by Combining Empirical Dynamic Modeling and Machine Learning Techniques
Jing Tian, Gangsheng Wang, Daifeng Xiang, et al.
Water Resources Research (2024) Vol. 60, Iss. 5
Open Access | Times Cited: 8
Plant-scale biogas production prediction based on multiple hybrid machine learning technique
Yi Zhang, Linhui Li, Zhonghao Ren, et al.
Bioresource Technology (2022) Vol. 363, pp. 127899-127899
Closed Access | Times Cited: 28
A data-augmentation approach to deriving long-term surface SO2 across Northern China: Implications for interpretable machine learning
Shifu Zhang, Tan Mi, Qinhuizi Wu, et al.
The Science of The Total Environment (2022) Vol. 827, pp. 154278-154278
Closed Access | Times Cited: 27
Development and validation of a machine-learning model for predicting the risk of death in sepsis patients with acute kidney injury
Lei Dong, Pei Liu, Zhili Qi, et al.
Heliyon (2024) Vol. 10, Iss. 9, pp. e29985-e29985
Open Access | Times Cited: 5
Predictive modeling of shallow tunnel behavior: Leveraging machine learning for maximum convergence displacement estimation
Danial Sheini Dashtgoli, Rasool Sadeghian, Ahmad Reza Mahboubi Ardakani, et al.
Transportation Geotechnics (2024) Vol. 47, pp. 101284-101284
Open Access | Times Cited: 5
Evaluation of best management practices for mitigating harmful algal blooms risk in an agricultural lake basin using a watershed model integrated with Bayesian Network approach
Dingwu Liu, Lei Huang, Jia Ling, et al.
Journal of Environmental Management (2024) Vol. 364, pp. 121433-121433
Closed Access | Times Cited: 5
Machine learning for high-precision simulation of dissolved organic matter in sewer: Overcoming data restrictions with generative adversarial networks
Feng Hou, Shuai Liu, Wan-Xin Yin, et al.
The Science of The Total Environment (2024) Vol. 947, pp. 174469-174469
Closed Access | Times Cited: 5
Understanding the Global Distribution of Groundwater Sulfate and Assessing Population at Risk
Chengyu Xiao, Shen Qu, Zhiyong Jason Ren, et al.
Environmental Science & Technology (2024) Vol. 58, Iss. 47, pp. 21002-21014
Closed Access | Times Cited: 5
Machine learning modeling of base flow generation potential: A case study of the combined application of BWM and Fallback bargaining algorithm
Ali Nasiri Khiavi
Journal of Hydrology (2024) Vol. 636, pp. 131220-131220
Closed Access | Times Cited: 4
Machine Learning to Assess and Support Safe Drinking Water Supply: A Systematic Review
Feng Feng, Yuanxun Zhang, Zhenru Chen, et al.
Journal of environmental chemical engineering (2024), pp. 114481-114481
Closed Access | Times Cited: 4
Evolutionary algorithm-based convolutional neural network for predicting heart diseases
Ali Abd Samir, Abdullah R. Rashwan, Karam M. Sallam, et al.
Computers & Industrial Engineering (2021) Vol. 161, pp. 107651-107651
Closed Access | Times Cited: 27
Prediction of Microcystis Occurrences and Analysis Using Machine Learning in High-Dimension, Low-Sample-Size and Imbalanced Water Quality Data
Masaya Mori, Roberto Gonzalez Flores, Yoshihiro Suzuki, et al.
Harmful Algae (2022) Vol. 117, pp. 102273-102273
Open Access | Times Cited: 19
Common issues of data science on the eco-environmental risks of emerging contaminants
Xiangang Hu, Dong Xu, Zhangjia Wang
Environment International (2025) Vol. 196, pp. 109301-109301
Open Access
Forecasting rare hydrological events by machine learning methods: case study of ice jams on the Pechora river
S. M. Iglin, V. M. Moreido, K. I. Golovnin
Lomonosov Geography Journal (2025) Vol. 80, Iss. №1, 2025, pp. 87-97
Closed Access
Spatial-and-local-aware deep learning approach for Ground-Level NO2 estimation in England with multisource data from satellite-based observations and chemical transport models
Siying Wang, Shuangyin Zhang, Dawei Wang, et al.
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 139, pp. 104506-104506
Closed Access
Spatiotemporal Dynamics and Drivers of Microbial Contaminants in Hurricane Florence Floodwaters
Emine N. Fidan, Brian J. Reich, R. E. Emanuel, et al.
ACS ES&T Water (2025)
Closed Access
GRU4ACE: Enhancing ACE inhibitory peptide prediction by integrating gated recurrent unit with multi‐source feature embeddings
Saeed Ahmed, Nalini Schaduangrat, Pramote Chumnanpuen, et al.
Protein Science (2025) Vol. 34, Iss. 6
Open Access
Prediction of 5‐day biochemical oxygen demand in the Buriganga River of Bangladesh using novel hybrid machine learning algorithms
Nabila Nafsin, Jin Li
Water Environment Research (2022) Vol. 94, Iss. 5
Closed Access | Times Cited: 15
Advances in Water, Air and Soil Pollution Monitoring, Modeling and Restoration
Alina Bărbulescu, Lucica Barbeș, Cristian Ștefan Dumitriu
Toxics (2024) Vol. 12, Iss. 4, pp. 244-244
Open Access | Times Cited: 3
Water quality estimates using machine learning techniques in an experimental watershed
David de Andrade Costa, Yared Bayissa, Kargean Vianna Barbosa, et al.
Journal of Hydroinformatics (2024) Vol. 26, Iss. 11, pp. 2798-2814
Closed Access | Times Cited: 3
Optimizing Models for the Prediction of One Step Ahead Extreme Flows to Wastewater Treatment Plants Using Different Synthetic Sampling Methods
Isaac Musaazi, Lu Liu, Andrew Shaw, et al.
(2025)
Closed Access
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