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:

Comparison of Multiple Machine Learning Methods for Correcting Groundwater Levels Predicted by Physics-Based Models
Guanyin Shuai, Yan Zhou, Jingli Shao, et al.
Sustainability (2024) Vol. 16, Iss. 2, pp. 653-653
Open Access | Times Cited: 6

Showing 6 citing articles:

Enhancing the accuracy of groundwater level prediction at different scales using spatio-temporal graph convolutional model
Long Chen, Dezheng Zhang, Jianwei Xu, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 2
Closed Access | Times Cited: 1

Groundwater dynamics clustering and prediction based on grey relational analysis and LSTM model: A case study in Beijing Plain, China
Yan Zhou, Qiulan Zhang, Guoying Bai, et al.
Journal of Hydrology Regional Studies (2024) Vol. 56, pp. 102011-102011
Open Access | Times Cited: 6

A review of recent hybridized machine learning methodologies for time series forecasting on water-related variables
Van Kwan Zhi Koh, Ye Li, Xing Yong Kek, et al.
Journal of Hydrology (2025), pp. 132909-132909
Closed Access

Hydrological simulation and forecasting of monthly groundwater levels using innovative artificial intelligence techniques for making policy decisions
N. R. Patel, M. Rao Vasala, Prakash Chandra Swain
International Journal of Energy and Water Resources (2025)
Closed Access

A new strategy for groundwater level prediction using a hybrid deep learning model under Ecological Water Replenishment
Zihao Jia, Qin Zhang, Bowen Shi, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 16, pp. 23951-23967
Closed Access | Times Cited: 2

Prediction of Capillary Pressure Curves Based on Particle Size Using Machine Learning
Xinghua Qi, Yuxuan Wei, Shimao Wang, et al.
Processes (2024) Vol. 12, Iss. 10, pp. 2306-2306
Open Access

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