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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:

Comparison of Machine Learning Algorithms for Flood Susceptibility Mapping
Seyd Teymoor Seydi, Yousef Kanani‐Sadat, Mahdi Hasanlou, et al.
Remote Sensing (2022) Vol. 15, Iss. 1, pp. 192-192
Open Access | Times Cited: 57

Showing 1-25 of 57 citing articles:

An XGBoost-SHAP approach to quantifying morphological impact on urban flooding susceptibility
Mo Wang, Yingxin Li, Haojun Yuan, et al.
Ecological Indicators (2023) Vol. 156, pp. 111137-111137
Open Access | Times Cited: 48
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: 41
AI-enabled strategies for climate change adaptation: protecting communities, infrastructure, and businesses from the impacts of climate change
Harshita Jain, Renu Dhupper, Anamika Shrivastava, et al.
Computational Urban Science (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 41
Machine learning models for gully erosion susceptibility assessment in the Tensift catchment, Haouz Plain, Morocco for sustainable development
Youssef Bammou, Brahim Benzougagh, Abdessalam Ouallali, et al.
Journal of African Earth Sciences (2024) Vol. 213, pp. 105229-105229
Open Access | Times Cited: 19
Flood susceptibility mapping through geoinformatics and ensemble learning methods, with an emphasis on the AdaBoost-Decision Tree algorithm, in Mazandaran, Iran
Maryam Jahanbani, Mohammad H. Vahidnia, Hossein Aghamohammadi, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 2, pp. 1433-1457
Closed Access | Times Cited: 13
Optimizing flood susceptibility assessment in semi-arid regions using ensemble algorithms: a case study of Moroccan High Atlas
Youssef Bammou, Brahim Benzougagh, Brahim Igmoullan, et al.
Natural Hazards (2024) Vol. 120, Iss. 8, pp. 7787-7816
Open Access | Times Cited: 13
Leveraging machine learning and open-source spatial datasets to enhance flood susceptibility mapping in transboundary river basin
Yogesh Bhattarai, Sunil Duwal, Sanjib Sharma, et al.
International Journal of Digital Earth (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 12
A hybrid of ensemble machine learning models with RFE and Boruta wrapper-based algorithms for flash flood susceptibility assessment
A. Habibi, M. R. Delavar, Mohammad Sadegh Sadeghian, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 122, pp. 103401-103401
Open Access | Times Cited: 32
Flood susceptibility assessment using machine learning approach in the Mohana-Khutiya River of Nepal
Menuka Maharjan, Sachin Timilsina, Santosh Ayer, et al.
Natural Hazards Research (2024) Vol. 4, Iss. 1, pp. 32-45
Open Access | Times Cited: 9
Enhancing Flood Risk Analysis in Harris County: Integrating Flood Susceptibility and Social Vulnerability Mapping
Hemal Dey, Wanyun Shao, Md. Munjurul Haque, et al.
Journal of Geovisualization and Spatial Analysis (2024) Vol. 8, Iss. 1
Closed 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: 7
Predicting Regional Heavy Precipitation Occurrences in the Southwest Iran Using Machine Learning Models and Atmospheric Variables
Kokab Shahgholian, Javad Bazrafshan, Parviz Irannejad, et al.
(2025)
Closed Access
Integrated Machine Learning Approaches for Landslide Susceptibility Mapping Along the Pakistan–China Karakoram Highway
Mohib Ullah, Haijun Qiu, Wenchao Huangfu, et al.
Land (2025) Vol. 14, Iss. 1, pp. 172-172
Open Access
Data Uncertainty of Flood Susceptibility Using Non-Flood Samples
Y. Zhang, Yongqiang Wei, Rui Yao, et al.
Remote Sensing (2025) Vol. 17, Iss. 3, pp. 375-375
Open Access
The Machine Learning-Based Mapping of Urban Pluvial Flood Susceptibility in Seoul Integrating Flood Conditioning Factors and Drainage-Related Data
Julieber T. Bersabe, Byong-Woon Jun
ISPRS International Journal of Geo-Information (2025) Vol. 14, Iss. 2, pp. 57-57
Open Access
A flash flood susceptibility prediction and partitioning method based on GeoDetector and random forest
Xinyue Ke, Ni Wang, Xiukai Yuan, et al.
Stochastic Environmental Research and Risk Assessment (2025)
Closed Access
Enhancing machine learning performance in cardiac surgery ICU: Hyperparameter optimization with metaheuristic algorithm
Ali Bahrami, Morteza Rakhshaninejad, Rouzbeh Ghousi, et al.
PLoS ONE (2025) Vol. 20, Iss. 2, pp. e0311250-e0311250
Open Access
Comparison of Machine Learning Models in Simulating Glacier Mass Balance: Insights from Maritime and Continental Glaciers in High Mountain Asia
Weiwei Ren, Zhongzheng Zhu, Yingzheng Wang, et al.
Remote Sensing (2024) Vol. 16, Iss. 6, pp. 956-956
Open Access | Times Cited: 5
Comparison of diverse machine learning algorithms for forest fire susceptibility mapping in Antalya, Türkiye
Hazan Alkan Akıncı, Halil Akıncı, Mustafa Zeybek
Advances in Space Research (2024) Vol. 74, Iss. 2, pp. 647-667
Closed Access | Times Cited: 5
A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping
Radhwan A. A. Saleh, Ahmed M. Al‐Areeq, Amran A. Al Aghbari, et al.
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 5
A Systematic Literature Review on Classification Machine Learning for Urban Flood Hazard Mapping
Maelaynayn El baida, Mohamed Hosni, Farid Boushaba, et al.
Water Resources Management (2024) Vol. 38, Iss. 15, pp. 5823-5864
Closed Access | Times Cited: 5
Flash Flood Susceptibility Mapping of North-east Depression of Bangladesh using Different GIS based Bivariate Statistical Models
Md. Sharafat Chowdhury
Watershed Ecology and the Environment (2024) Vol. 6, pp. 26-40
Open Access | Times Cited: 4
Integrating Machine Learning Models with Comprehensive Data Strategies and Optimization Techniques to Enhance Flood Prediction Accuracy: A Review
Adisa Hammed Akinsoji, Bashir Adelodun, Qudus Adeyi, et al.
Water Resources Management (2024) Vol. 38, Iss. 12, pp. 4735-4761
Closed Access | Times Cited: 4
Flood susceptibility modeling of the Karnali river basin of Nepal using different machine learning approaches
Sunil Duwal, Dedi Liu, Prachand Man Pradhan
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 12
A comparative spatial analysis of flood susceptibility mapping using boosting machine learning algorithms in Rathnapura, Sri Lanka
Kumudu Madhawa Kurugama, So Kazama, Yusuke Hiraga, et al.
Journal of Flood Risk Management (2024) Vol. 17, Iss. 2
Open Access | Times Cited: 4
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