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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:

A comparative study of machine learning and Fuzzy-AHP technique to groundwater potential mapping in the data-scarce region
Ranveer Kumar, Shyam Bihari Dwivedi, Shishir Gaur
Computers & Geosciences (2021) Vol. 155, pp. 104855-104855
Closed Access | Times Cited: 78

Showing 1-25 of 78 citing articles:

Groundwater Potential Zone Mapping Using Analytical Hierarchy Process and GIS in Muga Watershed, Abay Basin, Ethiopia
Tadele Melese, Tatek Belay
Global Challenges (2021) Vol. 6, Iss. 1
Open Access | Times Cited: 112
Assessment of groundwater potential modeling using support vector machine optimization based on Bayesian multi-objective hyperparameter algorithm
Duong Tran Anh, Manish Pandey, Varun Narayan Mishra, et al.
Applied Soft Computing (2022) Vol. 132, pp. 109848-109848
Closed Access | Times Cited: 52
Wildfire Risk Zone Mapping in Contrasting Climatic Conditions: An Approach Employing AHP and F-AHP Models
Aishwarya Sinha, S. Nikhil, R. S. Ajin, et al.
Fire (2023) Vol. 6, Iss. 2, pp. 44-44
Open Access | Times Cited: 33
Landslide Susceptibility Assessment of a Part of the Western Ghats (India) Employing the AHP and F-AHP Models and Comparison with Existing Susceptibility Maps
Sheela Bhuvanendran Bhagya, Anita Saji Sumi, S. Balaji, et al.
Land (2023) Vol. 12, Iss. 2, pp. 468-468
Open Access | Times Cited: 28
Performance evaluation of convolutional neural network and vision transformer models for groundwater potential mapping
Behnam Sadeghi, Ali Asghar Alesheikh, Ali Jafari, et al.
Journal of Hydrology (2025), pp. 132840-132840
Closed Access | Times Cited: 1
Modeling Drivers and Barriers of Artificial Intelligence Adoption: Insights from a Strategic Management Perspective
Sudatta Kar, Arpan Kumar Kar, Manmohan Prasad Gupta
Intelligent Systems in Accounting Finance & Management (2021) Vol. 28, Iss. 4, pp. 217-238
Closed Access | Times Cited: 56
Modelling and accessing land degradation vulnerability using remote sensing techniques and the analytical hierarchy process approach
Abebe Debele Tolche, Megersa Adugna Gurara, Quoc Bao Pham, et al.
Geocarto International (2021) Vol. 37, Iss. 24, pp. 7122-7142
Closed Access | Times Cited: 42
Groundwater potential mapping in the Central Highlands of Vietnam using spatially explicit machine learning
Tran Xuan Bien, Abolfazl Jaafari, Tran Van Phong, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 1, pp. 131-146
Closed Access | Times Cited: 18
Efficient Frequency ratio-Graphical adaptive tree-weighted support vector machine based ground water potential mapping utilizing remote sensing and GIS
Soundharyaa Shri Harini. R, V. Amudha, S. Vidhya Lakshmi
2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (2023), pp. 1-7
Closed Access | Times Cited: 18
Machine Learning-Based Assessment of Watershed Morphometry in Makran
Reza Derakhshani, Mojtaba Zaresefat, Vahid Nikpeyman, et al.
Land (2023) Vol. 12, Iss. 4, pp. 776-776
Open Access | Times Cited: 17
Combining high resolution input and stacking ensemble machine learning algorithms for developing robust groundwater potentiality models in Bisha watershed, Saudi Arabia
Javed Mallick, Swapan Talukdar, Mohd. Ahmed
Applied Water Science (2022) Vol. 12, Iss. 4
Open Access | Times Cited: 26
Introducing a novel approach for assessment of groundwater salinity hazard, vulnerability, and risk in a semiarid region
Hamidreza Gharechaee, Aliakbar Nazari Samani, Shahram Khalighi Sigaroodi, et al.
Ecological Informatics (2024) Vol. 81, pp. 102647-102647
Open Access | Times Cited: 5
Groundwater drought risk assessment in the semi-arid Kansai river basin, West Bengal, India using SWAT and machine learning models
Amit Bera, Nikhil Kumar Baranval, Rajwardhan Kumar, et al.
Groundwater for Sustainable Development (2024) Vol. 26, pp. 101254-101254
Closed Access | Times Cited: 5
Spatial prediction of groundwater potential by various novel boosting-based ensemble learning models in mountainous areas
Hanxiang Xiong, Xu Guo, Yuzhou Wang, et al.
Geocarto International (2023) Vol. 38, Iss. 1
Open Access | Times Cited: 12
Vulnerability evaluation utilizing AHP and an ensemble model in a few landslide-prone areas of the Western Ghats, India
S. J. Anchima, Ajayakumar Gokul, Chandini P. C. Senan, et al.
Environment Development and Sustainability (2023)
Closed Access | Times Cited: 11
Machine Learning-Based Water Management Strategies for Sustainable Groundwater Resources
Shubha G. Sanu, M. M. Math
SN Computer Science (2024) Vol. 5, Iss. 4
Closed Access | Times Cited: 4
Spatial Mapping and Prediction of Groundwater Quality Using Ensemble Learning Models and SHapley Additive exPlanations with Spatial Uncertainty Analysis
Shilong Yang, Danyuan Luo, Jiayao Tan, et al.
Water (2024) Vol. 16, Iss. 17, pp. 2375-2375
Open Access | Times Cited: 4
Identification of groundwater potential zones in data-scarce mountainous region using explainable machine learning
Kshitij Dahal, Sandesh Sharma, Amin Shakya, et al.
Journal of Hydrology (2023) Vol. 627, pp. 130417-130417
Closed Access | Times Cited: 10
Delineation of groundwater potential zone using geospatial tools and analytical hierarchy process (AHP) in the state of Uttarakhand, India
Atar Singh, Rajesh Kumar, Ramesh Kumar, et al.
Advances in Space Research (2023) Vol. 73, Iss. 6, pp. 2939-2954
Open Access | Times Cited: 10
Assessing the performance of machine learning and analytical hierarchy process (AHP) models for rainwater harvesting potential zone identification in hilly region, Bangladesh
Md. Mahmudul Hasan, Md. Talha, Most. Mitu Akter, et al.
Journal of Asian Earth Sciences X (2025) Vol. 13, pp. 100189-100189
Closed Access
Machine Learning Techniques in Hydrogeological Research
Song He, Xiaoping Zhou, Yuan Liu, et al.
Springer hydrogeology (2025), pp. 137-164
Closed Access
Machine learning–based habitat mapping of the invasive Prosopis juliflora in Sharjah, UAE
Alya Almaazmi, Rami Al‐Ruzouq, Abdallah Shanableh, et al.
Environmental Monitoring and Assessment (2025) Vol. 197, Iss. 4
Closed Access
An ensemble model of knowledge- and data-driven geospatial methods for mapping groundwater potential in a data-scarce, semi-arid fractured rock region
Stephen Fildes, Ian Clark, David Bruce, et al.
Applied Water Science (2025) Vol. 15, Iss. 4
Open Access
Integrated GIS, remote sensing, and analytical hierarchical process approaches to delineate groundwater storage zones in the Sub-Saharan region of Northern Ethiopia
Aniley T. Tesfaye
Heliyon (2025) Vol. 11, Iss. 10, pp. e43045-e43045
Closed Access
Delineation of groundwater potential zone by integrating groundwater quality parameters using geospatial techniques and multi-criteria decision analysis – a case study on Chennai coastal watershed, Tamil Nadu, India
Subramani Ravi, Karuppasamy Sudalaimuthu
Geocarto International (2022) Vol. 37, Iss. 27, pp. 16736-16768
Closed Access | Times Cited: 16
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