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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:

Interpretable tree-based ensemble model for predicting beach water quality
Lingbo Li, Jundong Qiao, Yu Guan, et al.
Water Research (2022) Vol. 211, pp. 118078-118078
Closed Access | Times Cited: 153

Showing 1-25 of 153 citing articles:

The role of deep learning in urban water management: A critical review
Guangtao Fu, Yiwen Jin, Siao Sun, et al.
Water Research (2022) Vol. 223, pp. 118973-118973
Open Access | Times Cited: 207
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: 78
Critical role of climate factors for groundwater potential mapping in arid regions: Insights from random forest, XGBoost, and LightGBM algorithms
Xu Guo, Xiaofan Gui, Hanxiang Xiong, et al.
Journal of Hydrology (2023) Vol. 621, pp. 129599-129599
Closed Access | Times Cited: 74
Cascade ensemble learning for multi-level reliability evaluation
Lu-Kai Song, Xueqin Li, Shun‐Peng Zhu, et al.
Aerospace Science and Technology (2024) Vol. 148, pp. 109101-109101
Closed Access | Times Cited: 30
Reliable water quality prediction and parametric analysis using explainable AI models
M. K. Nallakaruppan, E. Gangadevi, M. Lawanya Shri, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 23
Hybrid WT–CNN–GRU-based model for the estimation of reservoir water quality variables considering spatio-temporal features
Mohammad Zamani, Mohammad Reza Nikoo, Ghazi Al-Rawas, et al.
Journal of Environmental Management (2024) Vol. 358, pp. 120756-120756
Closed Access | Times Cited: 22
Interpretable predictive modelling of outlet temperatures in Central Alberta’s hydrothermal system using boosting-based ensemble learning incorporating Shapley Additive exPlanations (SHAP) approach
Ruyang Yu, Kai Zhang, Tao Li, et al.
Energy (2025), pp. 134738-134738
Closed Access | Times Cited: 2
Predicting and Analyzing Road Traffic Injury Severity Using Boosting-Based Ensemble Learning Models with SHAPley Additive exPlanations
Sheng Dong, Afaq Khattak, Irfan Ullah, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 5, pp. 2925-2925
Open Access | Times Cited: 68
A Review on Interpretable and Explainable Artificial Intelligence in Hydroclimatic Applications
Hakan Başağaoğlu, Debaditya Chakraborty, Cesar Do Lago, et al.
Water (2022) Vol. 14, Iss. 8, pp. 1230-1230
Open Access | Times Cited: 55
Machine learning framework for intelligent aeration control in wastewater treatment plants: Automatic feature engineering based on variation sliding layer
Yuqi Wang, Hongcheng Wang, Yunpeng Song, et al.
Water Research (2023) Vol. 246, pp. 120676-120676
Closed Access | Times Cited: 40
Does institutional quality affect CO2 emissions? Evidence from explainable artificial intelligence models
Nicolae Stef, Hakan Başağaoğlu, Debaditya Chakraborty, et al.
Energy Economics (2023) Vol. 124, pp. 106822-106822
Closed Access | Times Cited: 34
Machine Learning Models for Inverse Design of the Electrochemical Oxidation Process for Water Purification
Ye Sun, Zhiyuan Zhao, Hailong Tong, et al.
Environmental Science & Technology (2023) Vol. 57, Iss. 46, pp. 17990-18000
Closed Access | Times Cited: 32
Robust Runoff Prediction With Explainable Artificial Intelligence and Meteorological Variables From Deep Learning Ensemble Model
Junhao Wu, Zhaocai Wang, Jinghan Dong, et al.
Water Resources Research (2023) Vol. 59, Iss. 9
Closed Access | Times Cited: 31
Large-scale prediction of stream water quality using an interpretable deep learning approach
Hang Zheng, Yueyi Liu, Wenhua Wan, et al.
Journal of Environmental Management (2023) Vol. 331, pp. 117309-117309
Closed Access | Times Cited: 27
Spatiotemporal-aware machine learning approaches for dissolved oxygen prediction in coastal waters
Wenzhao Liang, Tongcun Liu, Yuntao Wang, et al.
The Science of The Total Environment (2023) Vol. 905, pp. 167138-167138
Closed Access | Times Cited: 23
Analyzing the operation reliability of aeroengine using Quick Access Recorder flight data
Wei-Huang Pan, Yunwen Feng, Cheng Lu, et al.
Reliability Engineering & System Safety (2023) Vol. 235, pp. 109193-109193
Closed Access | Times Cited: 22
Sustainable groundwater management in coastal cities: Insights from groundwater potential and vulnerability using ensemble learning and knowledge-driven models
P. M. Huang, Mengyao Hou, Tong Sun, et al.
Journal of Cleaner Production (2024) Vol. 442, pp. 141152-141152
Closed Access | Times Cited: 11
Interpretable machine learning on large samples for supporting runoff estimation in ungauged basins
Yuanhao Xu, Kairong Lin, Caihong Hu, et al.
Journal of Hydrology (2024) Vol. 639, pp. 131598-131598
Closed Access | Times Cited: 11
Quantifying the main and interactive effects of the dominant factors on the diurnal cycles of land surface temperature in typical urban functional zones
Jike Chen, Kaixin Wang, Peijun Du, et al.
Sustainable Cities and Society (2024) Vol. 114, pp. 105727-105727
Closed Access | Times Cited: 11
Revealing the drivers of surface ozone pollution by explainable machine learning and satellite observations in Hangzhou Bay, China
Tianen Yao, Sihua Lu, Yaqi Wang, et al.
Journal of Cleaner Production (2024) Vol. 440, pp. 140938-140938
Closed Access | Times Cited: 9
Coupling machine learning and theoretical models to compare key properties of biochar in adsorption kinetics rate and maximum adsorption capacity for emerging contaminants
Bingyou Liu, F. Xi, Huanjing Zhang, et al.
Bioresource Technology (2024) Vol. 402, pp. 130776-130776
Closed Access | Times Cited: 9
Machine learning-powered performance monitoring of proton exchange membrane water electrolyzers for enhancing green hydrogen production as a sustainable fuel for aviation industry
Shahin Alipour Bonab, Thomas D. Waite, Wenjuan Song, et al.
Energy Reports (2024) Vol. 12, pp. 2270-2282
Open Access | Times Cited: 9
Spatiotemporal drivers of urban water pollution: Assessment of 102 cities across the Yangtze River Basin
Yilin Zhao, Han-Jun Sun, Xiaodan Wang, et al.
Environmental Science and Ecotechnology (2024) Vol. 20, pp. 100412-100412
Open Access | Times Cited: 8
STFNIoT:Lightweight IoT Intrusion Detection Based on Explainable Analysis Using Spatiotemporal Fusion Networks
Hanlin Chen, Huan Liu, Wenjun Yang
Research Square (Research Square) (2025)
Closed Access | Times Cited: 1
Exploring the response of bacterial community functions to microplastic features in lake ecosystems through interpretable machine learning
Ming-Jia Li, Qi Liu, Jianjun Wang, et al.
Environmental Research (2025), pp. 121098-121098
Closed Access | Times Cited: 1
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