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:
A Comparative Analysis of Multiple Machine Learning Methods for Flood Routing in the Yangtze River
Liwei Zhou, Ling Kang
Water (2023) Vol. 15, Iss. 8, pp. 1556-1556
Open Access | Times Cited: 9
Liwei Zhou, Ling Kang
Water (2023) Vol. 15, Iss. 8, pp. 1556-1556
Open Access | Times Cited: 9
Showing 9 citing articles:
Hybridization of Stochastic Hydrological Models and Machine Learning Methods for Improving Rainfall-Runoff Modelling
Sianou Ezéckiel Houénafa, Olatunji Johnson, Erick Kiplangat Ronoh, et al.
Results in Engineering (2025), pp. 104079-104079
Open Access | Times Cited: 1
Sianou Ezéckiel Houénafa, Olatunji Johnson, Erick Kiplangat Ronoh, et al.
Results in Engineering (2025), pp. 104079-104079
Open Access | Times Cited: 1
Review of Machine Learning Methods for River Flood Routing
Li Li, Kyung Soo Jun
(2024)
Open Access | Times Cited: 2
Li Li, Kyung Soo Jun
(2024)
Open Access | Times Cited: 2
Review of Machine Learning Methods for River Flood Routing
Li Li, Kyung Soo Jun
Water (2024) Vol. 16, Iss. 2, pp. 364-364
Open Access | Times Cited: 2
Li Li, Kyung Soo Jun
Water (2024) Vol. 16, Iss. 2, pp. 364-364
Open Access | Times Cited: 2
Drought driving mechanism and risk situation prediction based on machine learning models in the Yellow River Basin, China
Ling Kang, Yunliang Wen, Liwei Zhou, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 5
Ling Kang, Yunliang Wen, Liwei Zhou, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 5
Research on Coupling Knowledge Embedding and Data-Driven Deep Learning Models for Runoff Prediction
Yanling Li, Junfang Wei, Qianxing Sun, et al.
Water (2024) Vol. 16, Iss. 15, pp. 2130-2130
Open Access | Times Cited: 1
Yanling Li, Junfang Wei, Qianxing Sun, et al.
Water (2024) Vol. 16, Iss. 15, pp. 2130-2130
Open Access | Times Cited: 1
Boosting flood routing prediction performance through a hybrid approach using empirical mode decomposition and neural networks: a case study of the Mera River in Ankara
Okan Mert Katipoğlu, Metin Sarıgöl
Water Science & Technology Water Supply (2023) Vol. 23, Iss. 11, pp. 4403-4415
Open Access | Times Cited: 3
Okan Mert Katipoğlu, Metin Sarıgöl
Water Science & Technology Water Supply (2023) Vol. 23, Iss. 11, pp. 4403-4415
Open Access | Times Cited: 3
Research on Flood Risk Control Methods and Reservoir Flood Control Operation Oriented towards Floodwater Utilization
Liwei Zhou, Ling Kang, Shuai Hou, et al.
Water (2023) Vol. 16, Iss. 1, pp. 43-43
Open Access | Times Cited: 2
Liwei Zhou, Ling Kang, Shuai Hou, et al.
Water (2023) Vol. 16, Iss. 1, pp. 43-43
Open Access | Times Cited: 2
Evaluating the Accuracy of Machine Learning, Deep Learning and Hybrid Algorithms for Flood Routing Calculations
Metin Sarıgöl
Pure and Applied Geophysics (2024)
Closed Access
Metin Sarıgöl
Pure and Applied Geophysics (2024)
Closed Access
Riverine flood hazard map prediction by neural networks
Zeda Yin, Arturo S. León
HydroResearch (2024) Vol. 8, pp. 139-151
Open Access
Zeda Yin, Arturo S. León
HydroResearch (2024) Vol. 8, pp. 139-151
Open Access
