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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:

Comparative Performance Assessment of Physical-Based and Data-Driven Machine-Learning Models for Simulating Streamflow: A Case Study in Three Catchments across the US
Aohan Jin, Quanrong Wang, Hongbin Zhan, et al.
Journal of Hydrologic Engineering (2024) Vol. 29, Iss. 2
Closed Access | Times Cited: 11

Showing 11 citing articles:

Improving Long-Term Flood Forecasting Accuracy Using Ensemble Deep Learning Models and an Attention Mechanism
Marjan Kordani, Mohammad Reza Nikoo, Mahmood Fooladi, et al.
Journal of Hydrologic Engineering (2024) Vol. 29, Iss. 6
Closed Access | Times Cited: 12
A state-of-the-art review of long short-term memory models with applications in hydrology and water resources
Zhong-kai Feng, J. Zhang, Wen-jing Niu
Applied Soft Computing (2024), pp. 112352-112352
Closed Access | Times Cited: 9
A hybrid self-adaptive DWT-WaveNet-LSTM deep learning architecture for karst spring forecasting
Renjie Zhou, Yanyan Zhang, Quanrong Wang, et al.
Journal of Hydrology (2024) Vol. 634, pp. 131128-131128
Closed Access | Times Cited: 8
Interpretable multi-step hybrid deep learning model for karst spring discharge prediction: Integrating temporal fusion transformers with ensemble empirical mode decomposition
Renjie Zhou, Quanrong Wang, Aohan Jin, et al.
Journal of Hydrology (2024), pp. 132235-132235
Closed Access | Times Cited: 4
Comparison of Multiple Indirect Approaches to Estimate Streamflow in the Osage and Severn Rivers
Sajjad M. Vatanchi, Mahmoud F. Maghrebi
Journal of Hydrologic Engineering (2025) Vol. 30, Iss. 3
Closed Access
Multi-scale dynamic spatiotemporal graph attention network for forecasting karst spring discharge
Renjie Zhou
Journal of Hydrology (2025), pp. 133289-133289
Closed Access
Hybrid Multivariate Machine Learning Models for Streamflow Forecasting: A Two-Stage Decomposition–Reconstruction Framework
Aohan Jin, Quanrong Wang, Renjie Zhou, et al.
Journal of Hydrologic Engineering (2024) Vol. 29, Iss. 5
Closed Access | Times Cited: 2
Impact of different hydrological models on hydroelectric operation planning
Jorge Daniel Páez Mendieta, Ieda Geriberto Hidalgo, Francesco Cioffi
Renewable Energy (2024) Vol. 232, pp. 120975-120975
Closed Access | Times Cited: 1
Advancing SWAT Model Calibration: A U-NSGA-III-Based Framework for Multi-Objective Optimization
Huihui Mao, Chen Wang, Yan He, et al.
Water (2024) Vol. 16, Iss. 21, pp. 3030-3030
Open Access | Times Cited: 1
Comparison of Multilayer Perceptron with an Optimal Activation Function and Long Short-Term Memory for Rainfall-Runoff Simulations and Ungauged Catchment Runoff Prediction
Mun-Ju Shin, Yong Jung
Water Resources Management (2024)
Closed Access | Times Cited: 1
Comparison of different machine learning methods in river streamflow estimation using isovel contours and hydraulic variables
Mahmoud F. Maghrebi, Sajjad M. Vatanchi
International Journal of River Basin Management (2024), pp. 1-18
Closed Access
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