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:

Efficacy of GIS-based AHP and data-driven intelligent machine learning algorithms for irrigation water quality prediction in an agricultural-mine district within the Lower Benue Trough, Nigeria
Michael E. Omeka, Ogbonnaya Igwe, Obialo S. Onwuka, et al.
Environmental Science and Pollution Research (2023) Vol. 31, Iss. 41, pp. 54204-54233
Closed Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

Assessment of groundwater suitability for sustainable irrigation: A comprehensive study using indexical, statistical, and machine learning approaches
Gobinder Singh, Jagdeep Singh, Owais Ali Wani, et al.
Groundwater for Sustainable Development (2023) Vol. 24, pp. 101059-101059
Closed Access | Times Cited: 52

A review of the status, challenges, trends, and prospects of groundwater quality assessment in Nigeria: an evidence-based meta-analysis approach
Michael E. Omeka, Arinze Longinus Ezugwu, Johnson C. Agbasi, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 15, pp. 22284-22307
Closed Access | Times Cited: 28

A novel predictive framework for water quality assessment based on socio-economic indicators and water leaving reflectance
Hao Chen, Ali P. Yunus
Groundwater for Sustainable Development (2025), pp. 101405-101405
Closed Access

Water potability classification based on hybrid stacked model and feature selection
Ahmed M. Elshewey, Rasha Y. Youssef, Hazem M. El‐Bakry, et al.
Environmental Science and Pollution Research (2025)
Closed Access

Analysis and prediction of groundwater quality using machine learning algorithm for irrigation purposes
Hemant Raheja, Arun Goel, Mahesh Pal
Environmental Earth Sciences (2025) Vol. 84, Iss. 7
Closed Access

Enhanced Water Quality Prediction: Application of Deep Neural Networks and Adaptive Neuro-Fuzzy Inference Systems to Assess Calcium Concentration
Moussa Attia, Zied Driss, Hany F. Abd‐Elhamid, et al.
Desalination and Water Treatment (2025), pp. 101193-101193
Open Access

Prediction of total dissolved solids, based on optimization of new hybrid SVM models
Fatemeh Akhoni Pourhosseini, Kumars Ebrahimi, M H Omid
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106780-106780
Closed Access | Times Cited: 7

Analyzing predictors of pearl millet supply chain using an artificial neural network
Nikita Dhankar, Srikanta Routroy, Satyendra Kumar Sharma
Journal of Modelling in Management (2024) Vol. 19, Iss. 4, pp. 1291-1315
Closed Access | Times Cited: 2

An Analysis of Preference Weights and Setting Priorities by Irrigation Advisory Services Users Based on the Analytic Hierarchy Process
Itzel Inti Maria Donati, Davide Viaggi, Zorica Srdjević, et al.
Agriculture (2023) Vol. 13, Iss. 8, pp. 1545-1545
Open Access | Times Cited: 5

An Integrated GIS-Based Reinforcement Learning Approach for Efficient Prediction of Disease Transmission in Aquaculture
Aristeidis Karras, Christos Karras, Spyros Sioutas, et al.
Information (2023) Vol. 14, Iss. 11, pp. 583-583
Open Access | Times Cited: 4

Application of Geospatial and Machine Learning Algorithms for Groundwater Quality Prediction Used for Irrigation Purposes
Hemant Raheja, Arun Goel, Mahesh Pal
Research Square (Research Square) (2024)
Open Access | Times Cited: 1

Modeling the vulnerability of water resources to pollution in a typical mining area, SE Nigeria using speciation, geospatial, and multi-path human health risk modeling approaches
Michael E. Omeka, Ogbonnaya Igwe, Obialo S. Onwuka, et al.
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 5, pp. 5923-5952
Closed Access | Times Cited: 1

Development and application of a comprehensive evaluation index system for groundwater quality evolution patterns
Xueqing Zhang, Long Wang, Liping Miao, et al.
Environmental Research (2024) Vol. 262, pp. 119896-119896
Closed Access | Times Cited: 1

Application of GIS and feedforward back-propagated ANN models for predicting the ecological and health risk of potentially toxic elements in soils in Northwestern Nigeria
Benjamin Odey Omang, Michael E. Omeka, Enah Asinya Asinya, et al.
Environmental Geochemistry and Health (2023) Vol. 45, Iss. 11, pp. 8599-8631
Closed Access | Times Cited: 3

Water Quality Prediction using Classification techniques on XGBoost, KNeighbors, SVC, Random Forest, AdaBoost, and GaussianNB Classifier
Kanwarpartap Singh Gill, Gaurav Tuteja, Vatsala Anand, et al.
(2023)
Closed Access | Times Cited: 2

Combining multiple numerical and chemometric models for assessing the microbial and pollution level of groundwater resources in a shallow alluvial aquifer, Southeastern Nigeria
Victor Chukwuemeka Aluma, Ogbonnaya Igwe, Michael E. Omeka, et al.
Arabian Journal of Geosciences (2024) Vol. 17, Iss. 7
Closed Access

State-of-the art-on irrigation water quality management using data-driven methods: Practical application, limitations, and prospective directions
Ali El Bilali, Abdeslam Taleb
Physics and Chemistry of the Earth Parts A/B/C (2024) Vol. 136, pp. 103794-103794
Closed Access

Application of geospatial and machine learning algorithms to predict (under certain limitations) the quality of groundwater used for irrigation purposes
Hemant Raheja, Arun Goel, Mahesh Pal
Water Science & Technology Water Supply (2024) Vol. 24, Iss. 11, pp. 3724-3743
Open Access

Smart solutions for maize farmers: Machine learning-enabled web applications for downy mildew management and enhanced crop yield in India
G. Jadesha, Edel Castelino, P. Mahadevu, et al.
European Journal of Agronomy (2024) Vol. 164, pp. 127441-127441
Closed Access

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