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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:

Machine Learning and Urban Drainage Systems: State-of-the-Art Review
Soon Ho Kwon, Joong Hoon Kim
Water (2021) Vol. 13, Iss. 24, pp. 3545-3545
Open Access | Times Cited: 21

Showing 21 citing articles:

Fast simulation and prediction of urban pluvial floods using a deep convolutional neural network model
Yaoxing Liao, Zhaoli Wang, Xiaohong Chen, et al.
Journal of Hydrology (2023) Vol. 624, pp. 129945-129945
Closed Access | Times Cited: 66
Hydraulic modelling of inland urban flooding: Recent advances
Emmanuel Mignot, Benjamin Dewals
Journal of Hydrology (2022) Vol. 609, pp. 127763-127763
Open Access | Times Cited: 65
Real-Time Urban Flood Forecasting Systems for Southeast Asia—A Review of Present Modelling and Its Future Prospects
Detchphol Chitwatkulsiri, Hitoshi Miyamoto
Water (2023) Vol. 15, Iss. 1, pp. 178-178
Open Access | Times Cited: 20
Geospatial modelling of floods: a literature review
Evangelina Avila-Aceves, Wenseslao Plata-Rocha, Sergio Alberto Monjardín-Armenta, et al.
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 11, pp. 4109-4128
Closed Access | Times Cited: 19
Machine learning applications in flood forecasting and predictions, challenges, and way-out in the perspective of changing environment
Vijendra Kumar, Kul Vaibhav Sharma, Nikunj K. Mangukiya, et al.
AIMS environmental science (2025) Vol. 12, Iss. 1, pp. 72-105
Open Access
Flood resilience through hybrid deep learning: Advanced forecasting for Taipei's urban drainage system
Li‐Chiu Chang, Ming-Ting Yang, Fi‐John Chang
Journal of Environmental Management (2025) Vol. 379, pp. 124835-124835
Closed Access
Prediction and early warning method of inundation process at waterlogging points based on Bayesian model average and data-driven
Yihong Zhou, Zening Wu, Hongshi Xu, et al.
Journal of Hydrology Regional Studies (2022) Vol. 44, pp. 101248-101248
Open Access | Times Cited: 17
A review of integrated multicriteria decision support analysis in the climate resilient infrastructure development
Parfait Iradukunda, Erastus Mwanaumo, Joel Kabika
Environmental and Sustainability Indicators (2023) Vol. 20, pp. 100312-100312
Open Access | Times Cited: 4
Developing data-driven learning models to predict urban stormwater runoff volume
Rachel Wood-Ponce, Ghada Diab, Zeyu Liu, et al.
Urban Water Journal (2024) Vol. 21, Iss. 5, pp. 549-564
Closed Access | Times Cited: 1
Understanding the impact of land use change on urban flood susceptibility mapping assessment: A review
Eggy Arya Giofandi, Boedi Tjahjono, Latief Mahir Rachman
Journal of Degraded and Mining Lands Management (2024) Vol. 11, Iss. 3, pp. 6025-6035
Open Access | Times Cited: 1
Real-time urban flood modeling: exploring the sub-grid approach for accurate simulation and hazard analysis
R. Reshma, N. Nithila Devi, Soumendra Nath Kuiry
Natural Hazards (2024) Vol. 120, Iss. 11, pp. 9609-9647
Closed Access | Times Cited: 1
Tunable linear feedback control of urban drainage systems using models defined purely from data
Travis Adrian Dantzer, Branko Kerkez
Water Science & Technology (2024) Vol. 89, Iss. 11, pp. 3147-3162
Open Access | Times Cited: 1
Developing meta-heuristic optimization based ensemble machine learning algorithms for hydraulic efficiency assessment of storm water grate inlets
Ömer Ekmekcioğlu, Eyyup Ensar Başakın, Mehmet Özger
Urban Water Journal (2022) Vol. 19, Iss. 10, pp. 1093-1108
Closed Access | Times Cited: 6
Modeling the 2D Inundation Simulation Based on the ANN-Derived Model with Real-Time Measurements at Roadside IoT Sensors
Shiang‐Jen Wu, Chih-Tsu Hsu, Jhih-Cyuan Shen, et al.
Water (2022) Vol. 14, Iss. 14, pp. 2189-2189
Open Access | Times Cited: 5
Drainage network flow anomaly classification based on XGBoost

Global NEST Journal (2023)
Open Access | Times Cited: 2
Remote Sensing and Artificial Intelligence for Urban Environmental Studies
Atiqur Rahman, Shouraseni Sen Roy, Swapan Talukdar, et al.
Springer eBooks (2023), pp. 1-12
Closed Access | Times Cited: 2
A two-phase approach for leak detection and localization in water distribution systems using wavelet decomposition and machine learning
Meriem Adraoui, Rida Azmi, Jérôme Chenal, et al.
Computers & Industrial Engineering (2024) Vol. 197, pp. 110534-110534
Closed Access
Machine learning-based rainfall forecasting in real-time optimal operation of urban drainage systems
Fatemeh Rezaei Aderyani, S. Jamshid Mousavi
Journal of Hydrology (2024), pp. 132118-132118
Closed Access
Drainage Pipeline Defect Detection System Based on Semantic Segmentation
Chun Du, Kunpeng Wang
Symmetry (2024) Vol. 16, Iss. 11, pp. 1477-1477
Open Access
Low global warming potential R1234yf in a mobile air-conditioning system: a study on performance prediction using different machine learning approaches
Rajendran Prabakaran, B. Gomathi, P. Jeyalakshmi, et al.
Journal of Thermal Analysis and Calorimetry (2024)
Closed Access
Machine Learning Algorithms Investigation for Urban Drainage Decision Systems: Overview
S. Boughandjioua, Fares Laouacheria, Nabiha Azizi
2022 International Conference on Decision Aid Sciences and Applications (DASA) (2023), pp. 306-313
Closed Access
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