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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:

Applicability of hybrid bionic optimization models with kernel-based extreme learning machine algorithm for predicting daily reference evapotranspiration: a case study in arid and semiarid regions, China
Long Zhao, Xinbo Zhao, Yuanze Li, et al.
Environmental Science and Pollution Research (2022) Vol. 30, Iss. 9, pp. 22396-22412
Closed Access | Times Cited: 12

Showing 12 citing articles:

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: 68
Intelligent Estimation of Soil Hydraulic Parameters: A Kelm-Pso Integrated Framework for Border Irrigation Optimization
Wen Zhou, Dan Bai, Yibo Li, et al.
(2025)
Closed Access
Evapotranspiration Prediction Method Based on K-Means Clustering and QPSO-MKELM Model
Chuansheng Zhang, Minglai Yang
Applied Sciences (2025) Vol. 15, Iss. 7, pp. 3530-3530
Open Access
Study on Monitoring SPAD Values for Multispatial Spatial Vertical Scales of Summer Maize Based on UAV Multispectral Remote Sensing
Jiangtao Ji, Nana Li, Hongwei Cui, et al.
Agriculture (2023) Vol. 13, Iss. 5, pp. 1004-1004
Open Access | Times Cited: 10
Gaussian mutation-alpine skiing optimization algorithm-recurrent attention unit-gated recurrent unit-extreme learning machine model: an advanced predictive model for predicting evaporation
Mohammad Ehteram, Fatemeh Barzegari Banadkooki, Mahdie Afshari Nia
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 5, pp. 1803-1830
Closed Access | Times Cited: 3
Variance-based sensitivity analysis of climate variability impact on crop yield using machine learning: A case study in Jordan
Yingqiang Xu, Abeer Albalawneh, Maysoon Al-Zoubi, et al.
Agricultural Water Management (2025) Vol. 313, pp. 109409-109409
Open Access
Monitoring Indicators for Comprehensive Growth of Summer Maize Based on UAV Remote Sensing
Hao Ma, Xue Li, Jiangtao Ji, et al.
Agronomy (2023) Vol. 13, Iss. 12, pp. 2888-2888
Open Access | Times Cited: 5
Daily runoff prediction during flood seasons based on the VMD–HHO–KELM model
Xianqi Zhang, Fang Liu, Qiuwen Yin, et al.
Water Science & Technology (2023) Vol. 88, Iss. 2, pp. 468-485
Open Access | Times Cited: 4
Optimization of Support Vector Machine with Biological Heuristic Algorithms for Estimation of Daily Reference Evapotranspiration Using Limited Meteorological Data in China
H. Alex Guo, Liance Wu, Xianlong Wang, et al.
Agronomy (2024) Vol. 14, Iss. 8, pp. 1780-1780
Open Access | Times Cited: 1
Machine Learning Methods Based on Limited Meteorological Data to Simulate Potential Evapotranspiration: A Case Study of Source Region of Yellow River Basin
Yinan Pei, Shengqi Jian, Guodong Zhang
International Journal of Climatology (2024)
Closed Access
Monthly runoff prediction of the lower Yellow River based on the VMD-SSA-KELM model
Xianqi Zhang, Jiawen Liu, He Ren
Research Square (Research Square) (2023)
Open Access
Machine Learning Methods Based on Limited Meteorological Data to Simulate Potential Evapotranspiration: A Case Study of Source Region of Yellow River Basin
Yinan Pei, Shengqi Jian, Guodong Zhang
(2023)
Closed Access
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