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:

Short-term daily reference evapotranspiration forecasting using temperature-based deep learning models in different climate zones in China
Lei Zhang, Xin Zhao, Ge Zhu, et al.
Agricultural Water Management (2023) Vol. 289, pp. 108498-108498
Open Access | Times Cited: 17

Showing 17 citing articles:

Innovative approach for predicting daily reference evapotranspiration using improved shallow and deep learning models in a coastal region: A comparative study
Hussam Eldin Elzain, Osman Abdalla, Mohammed Abdallah, et al.
Journal of Environmental Management (2024) Vol. 354, pp. 120246-120246
Closed Access | Times Cited: 17

Improving daily reference evapotranspiration forecasts: Designing AI-enabled recurrent neural networks based long short-term memory
Mumtaz Ali, Jesu Vedha Nayahi, Erfan Abdi, et al.
Ecological Informatics (2025), pp. 102995-102995
Open Access | Times Cited: 1

Using Artificial Intelligence Algorithms to Estimate and Short-Term Forecast the Daily Reference Evapotranspiration with Limited Meteorological Variables
Shih-Lun Fang, Y.-R. Lin, Sheng-Chih Chang, et al.
Agriculture (2024) Vol. 14, Iss. 4, pp. 510-510
Open Access | Times Cited: 4

Smart Irrigation for Coriander Plant: Saving Water with AI and IoT
Abhirup Paria, Arindam Giri, Subrata Dutta, et al.
Water Resources Management (2025)
Open Access

Coupled convolutional neural network with long short-term memory network for predicting lake water temperature
Huajian Yang, Chuqiang Chen, Xinhua Xue
Journal of Hydrology (2025), pp. 132878-132878
Closed Access

Estimating reference crop evapotranspiration using optimized empirical methods with a novel improved Grey Wolf Algorithm in four climatic regions of China
Juan Dong, Liwen Xing, Ningbo Cui, et al.
Agricultural Water Management (2023) Vol. 291, pp. 108620-108620
Open Access | Times Cited: 9

Egypt's water future: AI predicts evapotranspiration shifts across climate zones
Ali Mokhtar, Mohammed Magdy Hamed, Hongming He, et al.
Journal of Hydrology Regional Studies (2024) Vol. 56, pp. 101968-101968
Open Access | Times Cited: 2

Assessing forecast performance of daily reference evapotranspiration: A comparison of equations, machine and deep learning using weather forecasts
Haiyang Qian, Weiguang Wang, Gang Chen
Journal of Hydrology (2024), pp. 132101-132101
Closed Access | Times Cited: 1

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: 1

Smart irrigation for coriander plant: Saving water with AI and IoT
Abhirup Paria, Arindam Giri, Subrata Dutta, et al.
Research Square (Research Square) (2024)
Open Access

Reference Evapotranspiration Comparison of Any Two Cities Using Python and NASA Power’s API
Manita, Krishna Kumar Singh
World Environmental and Water Resources Congress 2011 (2024), pp. 327-340
Closed Access

Nonlinear comparative analysis of Greenland and Antarctica ice cores data
Berenice Rojo-Garibaldi, Alberto Isaac Aguilar-Hernández, Gustavo Martı́nez-Mekler
Chaos An Interdisciplinary Journal of Nonlinear Science (2024) Vol. 34, Iss. 8
Closed Access

Estimating and forecasting daily reference crop evapotranspiration in China with temperature-driven deep learning models
Jia Zhang, Yimin Ding, Lei Zhu, et al.
Agricultural Water Management (2024) Vol. 307, pp. 109268-109268
Open Access

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