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:

Formulation of Shannon entropy model averaging for groundwater level prediction using artificial intelligence models
Siamak Razzagh, Sina Sadeghfam, Ata Allah Nadiri, et al.
International Journal of Environmental Science and Technology (2021) Vol. 19, Iss. 7, pp. 6203-6220
Closed Access | Times Cited: 14

Showing 14 citing articles:

A review of the Artificial Intelligence (AI) based techniques for estimating reference evapotranspiration: Current trends and future perspectives
Pooja Goyal, Sunil Kumar, Rakesh Sharda
Computers and Electronics in Agriculture (2023) Vol. 209, pp. 107836-107836
Closed Access | Times Cited: 39

Shannon entropy of performance metrics to choose the best novel hybrid algorithm to predict groundwater level (case study: Tabriz plain, Iran)
Mohsen Saroughi, Ehsan Mirzania, Mohammed Achite, et al.
Environmental Monitoring and Assessment (2024) Vol. 196, Iss. 3
Open Access | Times Cited: 9

Groundwater Level Simulation Using Soft Computing Methods with Emphasis on Major Meteorological Components
Saeideh Samani, Meysam Vadiati, Farahnaz Azizi, et al.
Water Resources Management (2022) Vol. 36, Iss. 10, pp. 3627-3647
Closed Access | Times Cited: 36

Spatiotemporal Evolution and Nowcasting of the 2022 Yangtze River Mega-Flash Drought
Miaoling Liang, Xing Yuan, Shiyu Zhou, et al.
Water (2023) Vol. 15, Iss. 15, pp. 2744-2744
Open Access | Times Cited: 16

Assessment of Arctic Sea Ice Dynamics and Their Impacts on Precipitation Moisture Sources Using Deep Learning Approaches
Mojtaba Heydarizad, Zhongfang Liu, Melanie Parker, et al.
Environmental Technology & Innovation (2025), pp. 104088-104088
Open Access

Comparison of Three Imputation Methods for Groundwater Level Timeseries
Mara Meggiorin, Giulia Passadore, Silvia Bertoldo, et al.
Water (2023) Vol. 15, Iss. 4, pp. 801-801
Open Access | Times Cited: 7

Estimation of Unconfined Aquifer Transmissivity Using a Comparative Study of Machine Learning Models
zahra dashti, Mohammad Nakhaei, Meysam Vadiati, et al.
Water Resources Management (2023) Vol. 37, Iss. 12, pp. 4909-4931
Closed Access | Times Cited: 5

A comprehensive review of the salinity assessment in groundwater resources of Iran
Saeed Mohammadi Arasteh, Seyyed Mohammad Shoaei
Acta Geophysica (2023) Vol. 72, Iss. 1, pp. 385-403
Closed Access | Times Cited: 2

A Systematic Review of Neural Network Applications for Groundwater Level Prediction
Samuel Afful, Cyril D. Boateng, Emmanuel Ahene, et al.
EarthArXiv (California Digital Library) (2024)
Open Access

Simulating the effects of retreating Urmia Lake and increased evapotranspiration rates on the nearby unconfined aquifer
Zahra Abdollahi, Bakhtiar Feizizadeh, Behzad Shokati, et al.
Groundwater for Sustainable Development (2024) Vol. 26, pp. 101307-101307
Open Access

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