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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:

Multi-step ahead groundwater level forecasting in Grand Est, France: Comparison between stacked machine learning model and radial basis function neural network
Fabio Di Nunno, Carlo Giudicianni, Enrico Creaco, et al.
Groundwater for Sustainable Development (2023) Vol. 23, pp. 101042-101042
Closed Access | Times Cited: 11

Showing 11 citing articles:

Advanced evapotranspiration forecasting in Central Italy: Stacked MLP-RF algorithm and correlated Nystrom views with feature selection strategies
Francesco Granata, Fabio Di Nunno, Giovanni de Marinis
Computers and Electronics in Agriculture (2024) Vol. 220, pp. 108887-108887
Closed Access | Times Cited: 12
Dissolved Oxygen Forecasting in the Mississippi River: Advanced Ensemble Machine Learning Models
Francesco Granata, Senlin Zhu, Fabio Di Nunno
Environmental Science Advances (2024) Vol. 3, Iss. 11, pp. 1537-1551
Open Access | Times Cited: 8
A Combined Seasonal Mann–Kendall and Innovative Approach for the Trend Analysis of Streamflow Rate in Two Croatian Rivers
Mehmet Berkant Yıldız, Fabio Di Nunno, Bojan Đurin, et al.
Water (2024) Vol. 16, Iss. 10, pp. 1422-1422
Open Access | Times Cited: 7
Nature-inspired optimal tuning of input membership functions of fuzzy inference system for groundwater level prediction
Vipul Bhadani, Abhilash Singh, Vaibhav Kumar, et al.
Environmental Modelling & Software (2024) Vol. 175, pp. 105995-105995
Closed Access | Times Cited: 2
Analysis of land use/land cover changes and driving forces during the period 1992–2022: a case study of Jinan City, China
Lingye Tan, R. K., Ziyang Zhang
AQUA - Water Infrastructure Ecosystems and Society (2024) Vol. 73, Iss. 3, pp. 584-607
Open Access | Times Cited: 1
Mapping and modeling groundwater potential using machine learning, deep learning and ensemble learning models in the Saiss basin (Fez-Meknes Region, Morocco)
Hind Ragragui, My Hachem Aouragh, Abdellah El Hmaidi, et al.
Groundwater for Sustainable Development (2024) Vol. 26, pp. 101281-101281
Closed Access
Stacked Ensemble with Machine Learning Regressors on Optimal Features (SMOF) of hyperspectral sensor PRISMA for inland water turbidity prediction
Rajarshi Bhattacharjee, Shishir Gaur, Shard Chander, et al.
Environmental Science and Pollution Research (2024)
Closed Access
Integrating an interpolation technique and AI models using Bayesian model averaging to enhance groundwater level monitoring
Nan Wang, Zhixian Wang
Earth Science Informatics (2024) Vol. 18, Iss. 1
Closed Access
Deep Ensemble Learning-Based Sensor for Flotation Froth Image Recognition
Xiaojun Zhou, Yiping He
Sensors (2024) Vol. 24, Iss. 15, pp. 5048-5048
Open Access
Advanced Monthly Rainfall Forecasting in Southern Lazio: Integrating Climatic Indices, Classical or Deep Neural Networks, and a Feature Selection Algorithm
Fabio Di Nunno, Francesco Granata
Water Cycle (2024)
Open Access
Implementing augmented deep Machine learning for effective shallow water table management and forecasting
Mohammad Zeynoddin, Silvio J. Gumiere, Hossein Bonakdari
Journal of Hydrology (2024) Vol. 647, pp. 132371-132371
Closed Access
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