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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:

Assessing influential rainfall–runoff variables to simulate daily streamflow using random forest
Federico Vilaseca, Alberto Castro, Christian Chreties, et al.
Hydrological Sciences Journal (2023) Vol. 68, Iss. 12, pp. 1738-1753
Closed Access | Times Cited: 9

Showing 9 citing articles:

Spatio-temporal deep learning model for accurate streamflow prediction with multi-source data fusion
Zhaocai Wang, Nannan Xu, Xiaoguang Bao, et al.
Environmental Modelling & Software (2024) Vol. 178, pp. 106091-106091
Closed Access | Times Cited: 38
Enhancing environmental data imputation: A physically-constrained machine learning framework
Marcos Pastorini, Rafael Rodríguez, Lorena Etcheverry, et al.
The Science of The Total Environment (2024) Vol. 926, pp. 171773-171773
Closed Access | Times Cited: 2
Long-term natural streamflow forecasting under drought scenarios using data-intelligencw modeling
Lavínia D. Balthazar, Félix A. Miranda, Vinícius B.R. Cândido, et al.
Water Cycle (2024) Vol. 5, pp. 266-277
Open Access | Times Cited: 2
Hybridized machine learning models for phosphate pollution modeling in water systems for multiple uses
Tales Humberto de Aquino Boratto, Deivid E.D. Campos, Douglas L. Fonseca, et al.
Journal of Water Process Engineering (2024) Vol. 64, pp. 105598-105598
Closed Access | Times Cited: 2
Exploring the nexus between water quality and land use/land cover change in an urban watershed in Uruguay: a machine learning approach
Martina Pou, Marcos Pastorini, Jimena Alonso, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 35, pp. 48687-48705
Closed Access
River flow simulation based on empirical mode function signals and random forest algorithm
Vahed Eslamitabar, Farshad Ahmadi, Ahmad Sharafati, et al.
Acta Geophysica (2024)
Closed Access
Assessing spatiotemporal variations of soil organic carbon and its vulnerability to climate change: a bottom-up machine learning approach
Qichen Wang, Y. Shan, Wenbo Shi, et al.
Climate smart agriculture. (2024) Vol. 1, Iss. 2, pp. 100025-100025
Open Access
A probabilistic integration of LSTM and Gaussian Process Regression for uncertainty-aware reservoir water level predictions
Kshitij Tandon, Subhamoy Sen
Hydrological Sciences Journal (2024) Vol. 70, Iss. 1, pp. 144-161
Closed Access
Evaluating the Performance of Classification Algorithms for Land-Cover Classification
Marcos Pastorini, Angela Gorgoglione, Rafael Rodríguez, et al.
(2023), pp. 2240-2246
Closed Access | Times Cited: 1
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