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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:

General and regional cross-station assessment of machine learning models for estimating reference evapotranspiration
Yasser Zouzou, Hatice Çıtakoğlu
Acta Geophysica (2022) Vol. 71, Iss. 2, pp. 927-947
Closed Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Federated learning based reference evapotranspiration estimation for distributed crop fields
Muhammad Tausif, Muhammad Waseem Iqbal, Rab Nawaz Bashir, et al.
PLoS ONE (2025) Vol. 20, Iss. 2, pp. e0314921-e0314921
Open Access | Times Cited: 2
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: 60
Alp-valley and elevation effects on the reference evapotranspiration and the dominant climate controls in Red River Basin, China: Insights from geographical differentiation
Junxu Chen, Jihui Zhang, Jiabin Peng, et al.
Journal of Hydrology (2023) Vol. 620, pp. 129397-129397
Open Access | Times Cited: 35
A new regional reference evapotranspiration model based on quantile approximation of meteorological variables
Guomin Huang, Jianhua Dong, Lifeng Wu, et al.
Agricultural Water Management (2025) Vol. 308, pp. 109299-109299
Open Access | Times Cited: 1
Comparison of machine learning techniques and spatial distribution of daily reference evapotranspiration in Türkiye
Demet Kıran Yıldırım, Erdem Küçüktopçu, Bilal Cemek, et al.
Applied Water Science (2023) Vol. 13, Iss. 4
Open Access | Times Cited: 17
Machine learning algorithms for the prediction of drought conditions in the Wami River sub-catchment, Tanzania
Christossy Lalika, Aziz Ul Haq Mujahid, Mturi James, et al.
Journal of Hydrology Regional Studies (2024) Vol. 53, pp. 101794-101794
Open Access | Times Cited: 8
The consumer price index prediction using machine learning approaches: Evidence from the United States
Tien-Thinh Nguyen, Hong-Giang Nguyen, Jen‐Yao Lee, et al.
Heliyon (2023) Vol. 9, Iss. 10, pp. e20730-e20730
Open Access | Times Cited: 16
Assessment of machine learning algorithms and new hybrid multi-criteria analysis for flood hazard and mapping
Karim Solaimani, Shadman Darvishi, Fatemeh Shokrian
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 22, pp. 32950-32971
Closed Access | Times Cited: 5
APPLICATION OF MACHINE LEARNING MODELS AND GSA METHOD FOR DESIGNING STUD CONNECTORS
Guorui Sun, Jiayuan Kang, Jun Shi
Journal of Civil Engineering and Management (2024) Vol. 30, Iss. 4, pp. 373-390
Open Access | Times Cited: 4
A machine learning comparison of transportation mode changes from high-speed railway promotion in Thailand
Chinnakrit Banyong, Natthaporn Hantanong, Panuwat Wisutwattanasak, et al.
Results in Engineering (2024) Vol. 24, pp. 103110-103110
Open Access | Times Cited: 4
Prediction of Poisson’s ratio for a petroleum engineering application: Machine learning methods
Fahd Saeed Alakbari, Syed Mohammad Mahmood, Mohammed Abdalla Ayoub, et al.
PLoS ONE (2025) Vol. 20, Iss. 2, pp. e0317754-e0317754
Open Access
Hybrid machine learning for drought prediction at multiple time scales: a case study of Ağrı station, Türkiye
Hatice Çıtakoğlu, Gaye Aktürk, Vahdettin Demir
Acta Geophysica (2025)
Closed Access
Analyzing High-Speed Rail’s Transformative Impact on Public Transport in Thailand Using Machine Learning
Chinnakrit Banyong, Natthaporn Hantanong, Panuwat Wisutwattanasak, et al.
Infrastructures (2025) Vol. 10, Iss. 3, pp. 57-57
Open Access
A robust pressure drop prediction model in vertical multiphase flow: a machine learning approach
Fahd Saeed Alakbari, Mohammed Abdalla Ayoub, M. A. Awad, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Evaluating capabilities of the spline and cubic spline interpolation functions in reference evapotranspiration estimation implementing satellite image data
Parastoo Amirzehni, Saeed Samadianfard, AmirHossein Nazemi, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 4, pp. 3779-3795
Closed Access | Times Cited: 9
Assessment of machine learning methods predicting the axial vibration frequencies of microbars
Aiman Tariq, Büşra Uzun, Babür Deliktaş, et al.
ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik (2023) Vol. 104, Iss. 3
Closed Access | Times Cited: 9
Recurrent neural networks and sensitivity analysis for accurate monthly evapotranspiration estimation in the region of Fez, Morocco
Nisrine Lachgar, Achraf Berrajaa, Moad Essabbar, et al.
World Water Policy (2024) Vol. 10, Iss. 3, pp. 730-754
Closed Access | Times Cited: 3
Predicting deep well pump performance with machine learning methods during hydraulic head changes
Nuri Orhan
Heliyon (2024) Vol. 10, Iss. 11, pp. e31505-e31505
Open Access | Times Cited: 3
Improving Evapotranspiration Estimation in SWAT-Based Hydrologic Simulation through Data Assimilation in the SEBAL Algorithm
Omidreza Mikaeili, Mojtaba Shourian
Water Resources Management (2024)
Closed Access | Times Cited: 2
Combination of integrated machine learning model frameworks and infrared spectroscopy towards fast and interpretable characterization of model pyrolysis oil
Chao Chen, Rui Liang, Jingyu Zhu, et al.
Renewable Energy (2024), pp. 121434-121434
Closed Access | Times Cited: 2
Dynamic optimization can effectively improve the accuracy of reference evapotranspiration in southern China
Xiang Xiao, Ziniu Xiao, Xiaogang Liu, et al.
Computers and Electronics in Agriculture (2024) Vol. 230, pp. 109881-109881
Closed Access | Times Cited: 2
Providing a comprehensive understanding of missing data imputation processes in evapotranspiration-related research: a systematic literature review
Eyyup Ensar Başakın, Ömer Ekmekcioğlu, Mehmet Özger
Hydrological Sciences Journal (2023) Vol. 68, Iss. 14, pp. 2089-2104
Open Access | Times Cited: 4
Information Entropy-Based Hybrid Models Improve the Accuracy of Reference Evapotranspiration Forecast
Anzhen Qin, Zhilong Fan, Liuzeng Zhang
Advances in Meteorology (2024) Vol. 2024, pp. 1-13
Open Access | Times Cited: 1
Predicting the fundamental fluxes of an eddy-covariance station using machine learning methods
David García-Rodríguez, Pablo Catret Ruber, Domingo J. Iglesias Fuente, et al.
Ecological Informatics (2024) Vol. 81, pp. 102638-102638
Open Access | Times Cited: 1
Performance Evaluation of Regression-Based Machine Learning Models for Modeling Reference Evapotranspiration with Temperature Data
Maria J. Diamantopoulou, Dimitrios Papamichail
Hydrology (2024) Vol. 11, Iss. 7, pp. 89-89
Open Access | Times Cited: 1
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