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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:

Predicting and analyzing flood susceptibility using boosting-based ensemble machine learning algorithms with SHapley Additive exPlanations
Halit Enes Aydin, Muzaffer Can İban
Natural Hazards (2022) Vol. 116, Iss. 3, pp. 2957-2991
Closed Access | Times Cited: 80

Showing 1-25 of 80 citing articles:

Enhancing flood risk assessment through integration of ensemble learning approaches and physical-based hydrological modeling
Mohamed Saber, Tayeb Boulmaiz, Mawloud Guermoui, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 46
Explainable artificial intelligence in disaster risk management: Achievements and prospective futures
Saman Ghaffarian, Firouzeh Taghikhah, Holger R. Maier
International Journal of Disaster Risk Reduction (2023) Vol. 98, pp. 104123-104123
Open Access | Times Cited: 46
Research on Water Resource Modeling Based on Machine Learning Technologies
Liu Ze, Jingzhao Zhou, Xiaoyang Yang, et al.
Water (2024) Vol. 16, Iss. 3, pp. 472-472
Open Access | Times Cited: 19
Uncertainty Reduction in Flood Susceptibility Mapping Using Random Forest and eXtreme Gradient Boosting Algorithms in Two Tropical Desert Cities, Shibam and Marib, Yemen
Ali R. Al-Aizari, Hassan Alzahrani, Omar F. Althuwaynee, et al.
Remote Sensing (2024) Vol. 16, Iss. 2, pp. 336-336
Open Access | Times Cited: 14
Snow avalanche susceptibility mapping using novel tree-based machine learning algorithms (XGBoost, NGBoost, and LightGBM) with eXplainable Artificial Intelligence (XAI) approach
Muzaffer Can İban, Süleyman Sefa Bilgilioğlu
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 6, pp. 2243-2270
Closed Access | Times Cited: 31
A New Graph-Based Deep Learning Model to Predict Flooding with Validation on a Case Study on the Humber River
Victor Oliveira Santos, Paulo Alexandre Costa Rocha, John Scott, et al.
Water (2023) Vol. 15, Iss. 10, pp. 1827-1827
Open Access | Times Cited: 21
Urban waterlogging susceptibility assessment based on hybrid ensemble machine learning models: A case study in the metropolitan area in Beijing, China
Mingqi Yan, Jiarui Yang, Xiaoyong Ni, et al.
Journal of Hydrology (2024) Vol. 630, pp. 130695-130695
Closed Access | Times Cited: 12
A deep-learning-based tree species classification for natural secondary forests using unmanned aerial vehicle hyperspectral images and LiDAR
Ye Ma, Yuting Zhao, Jungho Im, et al.
Ecological Indicators (2024) Vol. 159, pp. 111608-111608
Open Access | Times Cited: 10
Explainability in wind farm planning: A machine learning framework for automatic site selection of wind farms
Atakan Bilgili, Tümay Arda, Batuhan Kılıç
Energy Conversion and Management (2024) Vol. 309, pp. 118441-118441
Closed Access | Times Cited: 9
Artificial Intelligence in Agricultural Mapping: A Review
Ramón Espinel, Gricelda Herrera-Franco, José Luis Rivadeneira García, et al.
Agriculture (2024) Vol. 14, Iss. 7, pp. 1071-1071
Open Access | Times Cited: 9
Novel optimized deep learning algorithms and explainable artificial intelligence for storm surge susceptibility modeling and management in a flood-prone island
Mohammed J. Alshayeb, Hoang Thi Hang, Ahmed Ali A. Shohan, et al.
Natural Hazards (2024) Vol. 120, Iss. 6, pp. 5099-5128
Closed Access | Times Cited: 8
Applying a 1D Convolutional Neural Network in Flood Susceptibility Assessments—The Case of the Island of Euboea, Greece
Paraskevas Tsangaratos, Ioanna Ilia, Aikaterini-Alexandra Chrysafi, et al.
Remote Sensing (2023) Vol. 15, Iss. 14, pp. 3471-3471
Open Access | Times Cited: 19
River ecological flow early warning forecasting using baseflow separation and machine learning in the Jiaojiang River Basin, Southeast China
Hao Chen, Saihua Huang, Yue‐Ping Xu, et al.
The Science of The Total Environment (2023) Vol. 882, pp. 163571-163571
Closed Access | Times Cited: 18
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: 6
Data-driven urban configuration optimization: An XGBoost-based approach for mitigating flood susceptibility and enhancing economic contribution
Haojun Yuan, Mo Wang, Dongqing Zhang, et al.
Ecological Indicators (2024) Vol. 166, pp. 112247-112247
Open Access | Times Cited: 5
Integrating machine learning and geospatial data analysis for comprehensive flood hazard assessment
Chiranjit Singha, Vikas Kumar Rana, Quoc Bao Pham, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 35, pp. 48497-48522
Open Access | Times Cited: 5
Flood risk in mountainous settlements: A new framework based on an interpretable NSGA-II-GB from a point-area duality perspective
Qihang Wu, Zhe Sun, Zhan Wang, et al.
Journal of Environmental Management (2025) Vol. 373, pp. 123842-123842
Closed Access
Importance of Geographic Information System (GIS) Application to Reduce the Impact of Flood Disasters in Malaysia: A Meta-Analysis
Adam Narashman Leeonis, Minhaz Farid Ahmed, Mazlin Mokhtar, et al.
Water (2025) Vol. 17, Iss. 2, pp. 181-181
Open Access
Revealing the nature of soil liquefaction using machine learning
Sufyan Ghani, Ishwor Thapa, Amrendra Kumar, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 2
Open Access
Quantifying Future Flood Risk in Guwahati Urban Watershed Using a Metaheuristic-Based Random Forest Model Under Climate Change Scenario
Ishita Afreen Ahmed, Swapan Talukdar, Shahfahad, et al.
(2025), pp. 129-147
Closed Access
Using Explainable Artificial Intelligence (Xai) to Understand Compound Flooding Arising from Rainstorms and Tides
Chengguang Lai, Yuhong Liao, Zhaoli Wang, et al.
(2025)
Closed Access
Improved flood risk assessment using multi-model ensemble machine-learning techniques in a tropical river basin of Southern India
A.L. Achu, C. D. Aju, M. C. Raicy, et al.
Physical Geography (2025), pp. 1-29
Closed Access
Evaluating the uncertainty in landslide susceptibility prediction: effect of spatial data variability and evaluation unit choices
Shengwu Qin, Jiasheng Cao, Jingyu Yao, et al.
Bulletin of Engineering Geology and the Environment (2025) Vol. 84, Iss. 3
Closed Access
Contrast or Diversity: Non-Flood sampling in urban flood susceptibility modelling
Huabing Huang, Zhiwen Tao, Jiayin Zhan, et al.
Journal of Hydrology (2025), pp. 133053-133053
Closed Access
Formation Mechanism and Response Strategies for Urban Waterlogging: A Comprehensive Review
Y. Nie, Junhao Chen, X. Xiong, et al.
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 3037-3037
Open Access
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