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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:

Advanced machine learning algorithms for flood susceptibility modeling — performance comparison: Red Sea, Egypt
Ahmed M. Youssef, Hamid Reza Pourghasemi, Bosy A. El‐Haddad
Environmental Science and Pollution Research (2022) Vol. 29, Iss. 44, pp. 66768-66792
Closed Access | Times Cited: 18

Showing 18 citing articles:

Flood susceptibility mapping using machine learning boosting algorithms techniques in Idukki district of Kerala India
Subbarayan Saravanan, Devanantham Abijith, Nagireddy Masthan Reddy, et al.
Urban Climate (2023) Vol. 49, pp. 101503-101503
Closed Access | Times Cited: 57
A novel deep learning framework for landslide susceptibility assessment using improved deep belief networks with the intelligent optimization algorithm
Shaoqiang Meng, Zhenming Shi, Gang Li, et al.
Computers and Geotechnics (2024) Vol. 167, pp. 106106-106106
Closed Access | Times Cited: 22
Urban flood susceptibility mapping using frequency ratio and multiple decision tree-based machine learning models
Hemal Dey, Wanyun Shao, Hamid Moradkhani, et al.
Natural Hazards (2024) Vol. 120, Iss. 11, pp. 10365-10393
Closed Access | Times Cited: 9
Solving the spatial extrapolation problem in flood susceptibility using hybrid machine learning, remote sensing, and GIS
Huu Duy Nguyen, Quoc‐Huy Nguyen, Quang‐Thanh Bui
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 12, pp. 18701-18722
Closed Access | Times Cited: 8
Assessment of environmental geological disaster susceptibility under a multimodel comparison to aid in the sustainable development of the regional economy
Cui Wang, Xuedong Wang, Heyong Zhang, et al.
Environmental Science and Pollution Research (2022) Vol. 30, Iss. 3, pp. 6573-6591
Closed Access | Times Cited: 26
Robustness of machine learning algorithms to generate flood susceptibility maps for watersheds in Jordan
Mohanned S. Al-Sheriadeh, Mohammad A. Daqdouq
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 4
Spatial Estimation of Regional PM2.5 Concentrations with GWR Models Using PCA and RBF Interpolation Optimization
Youbing Tang, Shaofeng Xie, Liangke Huang, et al.
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5626-5626
Open Access | Times Cited: 17
An assessment on the off-road trafficability using a quantitative rule method with geographical and geological data
K. L. He, Yusen Dong, Wei Han, et al.
Computers & Geosciences (2023) Vol. 177, pp. 105355-105355
Closed Access | Times Cited: 8
Flood susceptibility mapping to improve models of species distributions
Elham Ebrahimi, Miguel B. Araújo, Babak Naimi
Ecological Indicators (2023) Vol. 157, pp. 111250-111250
Open Access | Times Cited: 8
Mapping flood susceptibility with PROMETHEE multi-criteria analysis method
Konstantinos Plataridis, Zisis Mallios
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 28, pp. 41267-41289
Closed Access | Times Cited: 2
Assessing Critical Flood-Prone Districts and Optimal Shelter Zones in the Brahmaputra Valley: Strategies for Effective Flood Risk Management
Jatan Debnath, Dhrubajyoti Sahariah, Gowhar Meraj, et al.
Physics and Chemistry of the Earth Parts A/B/C (2024), pp. 103772-103772
Closed Access | Times Cited: 2
Simulating flood risk in Tampa Bay using a machine learning driven approach
Hemal Dey, Md. Munjurul Haque, Wanyun Shao, et al.
npj natural hazards. (2024) Vol. 1, Iss. 1
Open Access | Times Cited: 2
Develop of a machine learning model to evaluate the hazards of sand dunes
Hanaa A. Megahed, Abd El‐Hay A. Farrag, Hossam M. GabAllah, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 5, pp. 4001-4025
Closed Access | Times Cited: 1
Analysis of the utilization of machine learning to map flood susceptibility
Ali Pourzangbar, Peter Oberle, Andreas Kron, et al.
(2024)
Closed Access | Times Cited: 1
Futuristic flood risks assessment, in the Upper Vellar Basin, integrating AHP and bivariate analysis
M. Subbulakshmi, Sachikanta Nanda
Advances in Space Research (2024) Vol. 74, Iss. 11, pp. 5395-5416
Closed Access | Times Cited: 1
SAR-driven flood inventory and multi-factor ensemble susceptibility modelling using machine learning frameworks
Krishnagopal Halder, Anitabha Ghosh, Amit Kumar Srivastava, et al.
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Comprehensive evaluation of machine learning algorithms for flood susceptibility mapping in Wardha River sub-basin, India
Asheesh Sharma, Sudhanshu Nerkar, Rishit Banyal, et al.
Acta Geophysica (2024)
Closed Access | Times Cited: 1
Exploring a form of pixel-based information value model for flood probability assessment and geo-visualization over an East African basin: a case of Nyabarongo in Rwanda
Richard Mind’je, Lanhai Li, Patient Mindje Kayumba, et al.
Environmental Earth Sciences (2023) Vol. 82, Iss. 17
Closed Access | Times Cited: 4
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