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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:

Data intelligence and hybrid metaheuristic algorithms-based estimation of reference evapotranspiration
Ahmed Elbeltagi, Ali Raza, Yongguang Hu, et al.
Applied Water Science (2022) Vol. 12, Iss. 7
Open Access | Times Cited: 57

Showing 1-25 of 57 citing articles:

An Integrated Statistical-Machine Learning Approach for Runoff Prediction
Abhinav Kumar Singh, Pankaj Kumar, Rawshan Ali, et al.
Sustainability (2022) Vol. 14, Iss. 13, pp. 8209-8209
Open Access | Times Cited: 72
Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR) models
Ahmed Elbeltagi, Chaitanya B. Pande, Manish Kumar, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 15, pp. 43183-43202
Closed Access | Times Cited: 66
Modeling Potential Evapotranspiration by Improved Machine Learning Methods Using Limited Climatic Data
Reham R. Mostafa, Özgür Kişi, Rana Muhammad Adnan, et al.
Water (2023) Vol. 15, Iss. 3, pp. 486-486
Open Access | Times Cited: 66
Comparative Assessment of Improved SVM Method under Different Kernel Functions for Predicting Multi-scale Drought Index
Chaitanya B. Pande, Nand Lal Kushwaha, Israel R. Orimoloye, et al.
Water Resources Management (2023) Vol. 37, Iss. 3, pp. 1367-1399
Open Access | Times Cited: 46
Comparative assessment of empirical and hybrid machine learning models for estimating daily reference evapotranspiration in sub-humid and semi-arid climates
Siham Acharki, Ali Raza, Dinesh Kumar Vishwakarma, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Modeling monthly reference evapotranspiration process in Turkey: application of machine learning methods
Savaş Bayram, Hatice Çıtakoğlu
Environmental Monitoring and Assessment (2022) Vol. 195, Iss. 1
Closed Access | Times Cited: 57
Pre- and post-dam river water temperature alteration prediction using advanced machine learning models
Dinesh Kumar Vishwakarma, Rawshan Ali, Shakeel Ahmad Bhat, et al.
Environmental Science and Pollution Research (2022) Vol. 29, Iss. 55, pp. 83321-83346
Open Access | Times Cited: 41
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: 37
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing
M. J. Jiménez-Navarro, M. Martínez-Ballesteros, Isabel Sofía Brito, et al.
(2023)
Open Access | Times Cited: 34
Application of Innovative Machine Learning Techniques for Long-Term Rainfall Prediction
Suman Markuna, Pankaj Kumar, Rawshan Ali, et al.
Pure and Applied Geophysics (2023) Vol. 180, Iss. 1, pp. 335-363
Closed Access | Times Cited: 33
Forecasting vapor pressure deficit for agricultural water management using machine learning in semi-arid environments
Ahmed Elbeltagi, Aman Srivastava, Jinsong Deng, et al.
Agricultural Water Management (2023) Vol. 283, pp. 108302-108302
Open Access | Times Cited: 33
Combination of discretization regression with data-driven algorithms for modeling irrigation water quality indices
Dimple Dimple, Pradeep Kumar Singh, Jitendra Rajput, et al.
Ecological Informatics (2023) Vol. 75, pp. 102093-102093
Closed Access | Times Cited: 30
Forecasting of stage-discharge in a non-perennial river using machine learning with gamma test
Dinesh Kumar Vishwakarma, Alban Kuriqi, Salwan Ali Abed, et al.
Heliyon (2023) Vol. 9, Iss. 5, pp. e16290-e16290
Open Access | Times Cited: 28
A Novel Hybrid Algorithms for Groundwater Level Prediction
Mohsen Saroughi, Ehsan Mirzania, Dinesh Kumar Vishwakarma, et al.
Iranian Journal of Science and Technology Transactions of Civil Engineering (2023) Vol. 47, Iss. 5, pp. 3147-3164
Closed Access | Times Cited: 27
A novel hybrid AIG-SVR model for estimating daily reference evapotranspiration
Ehsan Mirzania, Dinesh Kumar Vishwakarma, Quynh-Anh Thi Bui, et al.
Arabian Journal of Geosciences (2023) Vol. 16, Iss. 5
Closed Access | Times Cited: 25
Global-scale water security and desertification management amidst climate change
Shubham Jain, Aman Srivastava, Leena Khadke, et al.
Environmental Science and Pollution Research (2024)
Closed Access | Times Cited: 13
Evaluation of CatBoost Method for Predicting Weekly Pan Evaporation in Subtropical and Sub-Humid Regions
Dinesh Kumar Vishwakarma, Pankaj Kumar, Krishna Kumar Yadav, et al.
Pure and Applied Geophysics (2024) Vol. 181, Iss. 2, pp. 719-747
Open Access | Times Cited: 12
Daily suspended sediment yield estimation using soft-computing algorithms for hilly watersheds in a data-scarce situation: a case study of Bino watershed, Uttarakhand
Paramjeet Singh Tulla, Pravendra Kumar, Dinesh Kumar Vishwakarma, et al.
Theoretical and Applied Climatology (2024) Vol. 155, Iss. 5, pp. 4023-4047
Closed Access | Times Cited: 11
Use of gene expression programming to predict reference evapotranspiration in different climatic conditions
Ali Raza, Dinesh Kumar Vishwakarma, Siham Acharki, et al.
Applied Water Science (2024) Vol. 14, Iss. 7
Open Access | Times Cited: 8
Evaluation of Data-driven Hybrid Machine Learning Algorithms for Modelling Daily Reference Evapotranspiration
Nand Lal Kushwaha, Jitendra Rajput, D.R. Sena, et al.
ATMOSPHERE-OCEAN (2022) Vol. 60, Iss. 5, pp. 519-540
Closed Access | Times Cited: 28
Forecasting actual evapotranspiration without climate data based on stacked integration of DNN and meta-heuristic models across China from 1958 to 2021
Ahmed Elbeltagi, Aman Srivastava, Penghan Li, et al.
Journal of Environmental Management (2023) Vol. 345, pp. 118697-118697
Closed Access | Times Cited: 18
Forecasting Long-Series Daily Reference Evapotranspiration Based on Best Subset Regression and Machine Learning in Egypt
Ahmed Elbeltagi, Aman Srivastava, Abdullah Hassan Al-Saeedi, et al.
Water (2023) Vol. 15, Iss. 6, pp. 1149-1149
Open Access | Times Cited: 17
Modeling Daily Reference Evapotranspiration from Climate Variables: Assessment of Bagging and Boosting Regression Approaches
T. R. Jayashree, N. V. Subba Reddy, U. Dinesh Acharya
Water Resources Management (2023) Vol. 37, Iss. 3, pp. 1013-1032
Open Access | Times Cited: 16
Modeling climate change impacts on vector-borne disease using machine learning models: Case study of Visceral leishmaniasis (Kala-azar) from Indian state of Bihar
Shubham Kumar, Aman Srivastava, Rajib Maity
Expert Systems with Applications (2023) Vol. 237, pp. 121490-121490
Closed Access | Times Cited: 14
Revolutionizing the Future of Hydrological Science: Impact of Machine Learning and Deep Learning amidst Emerging Explainable AI and Transfer Learning
Rajib Maity, Aman Srivastava, Subharthi Sarkar, et al.
Applied Computing and Geosciences (2024) Vol. 24, pp. 100206-100206
Open Access | Times Cited: 4
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