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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:

Exploring effectiveness of frequency ratio and support vector machine models in storm surge flood susceptibility assessment: A study of Sundarban Biosphere Reserve, India
Mehebub Sahana, Sufia Rehman, Haroon Sajjad, et al.
CATENA (2020) Vol. 189, pp. 104450-104450
Closed Access | Times Cited: 134

Showing 1-25 of 134 citing articles:

Flood susceptibility modelling using advanced ensemble machine learning models
Abu Reza Md. Towfiqul Islam, Swapan Talukdar, Susanta Mahato, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 3, pp. 101075-101075
Open Access | Times Cited: 427
Assessment and prediction of carbon sequestration using Markov chain and InVEST model in Sariska Tiger Reserve, India
Deepakshi Babbar, G. Areendran, Mehebub Sahana, et al.
Journal of Cleaner Production (2020) Vol. 278, pp. 123333-123333
Closed Access | Times Cited: 210
Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms
Swapan Talukdar, Bonosri Ghose, Shahfahad, et al.
Stochastic Environmental Research and Risk Assessment (2020) Vol. 34, Iss. 12, pp. 2277-2300
Closed Access | Times Cited: 184
Flood Susceptibility Mapping through the GIS-AHP Technique Using the Cloud
Kishore Chandra Swain, Chiranjit Singha, L. K. Nayak
ISPRS International Journal of Geo-Information (2020) Vol. 9, Iss. 12, pp. 720-720
Open Access | Times Cited: 175
Flood susceptibility mapping of the Western Ghat coastal belt using multi-source geospatial data and analytical hierarchy process (AHP)
Sumit Das
Remote Sensing Applications Society and Environment (2020) Vol. 20, pp. 100379-100379
Closed Access | Times Cited: 157
Flood susceptibility mapping by integrating frequency ratio and index of entropy with multilayer perceptron and classification and regression tree
Yi Wang, Zhice Fang, Haoyuan Hong, et al.
Journal of Environmental Management (2021) Vol. 289, pp. 112449-112449
Closed Access | Times Cited: 122
A novel flood risk management approach based on future climate and land use change scenarios
Huu Duy Nguyen, Quoc‐Huy Nguyen, Dinh Kha Dang, et al.
The Science of The Total Environment (2024) Vol. 921, pp. 171204-171204
Closed Access | Times Cited: 26
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: 18
Demand forecasting with color parameter in retail apparel industry using artificial neural networks (ANN) and support vector machines (SVM) methods
İlker Güven, Fuat Şimşir
Computers & Industrial Engineering (2020) Vol. 147, pp. 106678-106678
Closed Access | Times Cited: 108
Flood susceptibility assessment based on a novel random Naïve Bayes method: A comparison between different factor discretization methods
Xianzhe Tang, Jiufeng Li, Minnan Liu, et al.
CATENA (2020) Vol. 190, pp. 104536-104536
Closed Access | Times Cited: 101
Application of stacking hybrid machine learning algorithms in delineating multi-type flooding in Bangladesh
Mahfuzur Rahman, Ningsheng Chen, Ahmed Elbeltagi, et al.
Journal of Environmental Management (2021) Vol. 295, pp. 113086-113086
Closed Access | Times Cited: 88
Exploring machine learning potential for climate change risk assessment
Federica Zennaro, Elisa Furlan, Christian Simeoni, et al.
Earth-Science Reviews (2021) Vol. 220, pp. 103752-103752
Closed Access | Times Cited: 82
Assessment of the performance of GIS-based analytical hierarchical process (AHP) approach for flood modelling in Uttar Dinajpur district of West Bengal, India
Rajib Mitra, Piu Saha, Jayanta Das
Geomatics Natural Hazards and Risk (2022) Vol. 13, Iss. 1, pp. 2183-2226
Open Access | Times Cited: 66
Flood susceptibility zonation using advanced ensemble machine learning models within Himalayan foreland basin
Supriya Ghosh, Soumik Saha, Biswajit Bera
Natural Hazards Research (2022) Vol. 2, Iss. 4, pp. 363-374
Open Access | Times Cited: 65
Flood vulnerability and resilience assessment in China based on super-efficiency DEA and SBM-DEA methods
Yuying Yang, Haixiang Guo, Deyun Wang, et al.
Journal of Hydrology (2021) Vol. 600, pp. 126470-126470
Closed Access | Times Cited: 59
Development of flood hazard map and emergency relief operation system using hydrodynamic modeling and machine learning algorithm
Mahfuzur Rahman, Ningsheng Chen, Md Monirul Islam, et al.
Journal of Cleaner Production (2021) Vol. 311, pp. 127594-127594
Closed Access | Times Cited: 58
Hybrid Models Incorporating Bivariate Statistics and Machine Learning Methods for Flash Flood Susceptibility Assessment Based on Remote Sensing Datasets
Jun Liu, Jiyan Wang, Junnan Xiong, et al.
Remote Sensing (2021) Vol. 13, Iss. 23, pp. 4945-4945
Open Access | Times Cited: 57
Comparative study of convolutional neural network (CNN) and support vector machine (SVM) for flood susceptibility mapping: a case study at Ras Gharib, Red Sea, Egypt
Ahmed M. Youssef, Biswajeet Pradhan, Abhirup Dikshit, et al.
Geocarto International (2022) Vol. 37, Iss. 26, pp. 11088-11115
Closed Access | Times Cited: 52
Comparison of statistical and MCDM approaches for flood susceptibility mapping in northern Iran
S. Mostafa Mousavi, Behzad Ataie‐Ashtiani, Seiyed Mossa Hosseini
Journal of Hydrology (2022) Vol. 612, pp. 128072-128072
Closed Access | Times Cited: 44
Multi-hazard spatial modeling via ensembles of machine learning and meta-heuristic techniques
Mojgan Bordbar, Hossein Aghamohammadi, Hamid Reza Pourghasemi, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 42
Know to Predict, Forecast to Warn: A Review of Flood Risk Prediction Tools
Kwesi Twum Antwi-Agyakwa, Mawuli Afenyo, Donatus Bapentire Angnuureng
Water (2023) Vol. 15, Iss. 3, pp. 427-427
Open Access | Times Cited: 25
Forecasting of compound ocean-fluvial floods using machine learning
Sogol Moradian, Amir AghaKouchak, Salem Gharbia, et al.
Journal of Environmental Management (2024) Vol. 364, pp. 121295-121295
Closed Access | Times Cited: 14
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: 11
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: 9
Leveraging GIS-based AHP, remote sensing, and machine learning for susceptibility assessment of different flood types in peshawar, Pakistan
Muhammad Tayyab, Muhammad Hussain, Jiquan Zhang, et al.
Journal of Environmental Management (2024) Vol. 371, pp. 123094-123094
Closed Access | Times Cited: 9
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