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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:

Artificial Neural Networks for Flood Susceptibility Mapping in Data-Scarce Urban Areas
Fatemeh Falah, Omid Rahmati, Mohammad Rostami, et al.
Elsevier eBooks (2019), pp. 323-336
Closed Access | Times Cited: 145

Showing 1-25 of 145 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
GIS-based comparative assessment of flood susceptibility mapping using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and logistic regression: A case of Topľa basin, Slovakia
Sk Ajim Ali, Farhana Parvin, Quoc Bao Pham, et al.
Ecological Indicators (2020) Vol. 117, pp. 106620-106620
Open Access | Times Cited: 264
Prediction of groundwater quality using efficient machine learning technique
Sudhakar Singha, Srinivas Pasupuleti, Soumya S. Singha, et al.
Chemosphere (2021) Vol. 276, pp. 130265-130265
Closed Access | Times Cited: 252
Flood Susceptibility Assessment in Bangladesh Using Machine Learning and Multi-criteria Decision Analysis
Mahfuzur Rahman, Chen Ningsheng, Md Monirul Islam, et al.
Earth Systems and Environment (2019) Vol. 3, Iss. 3, pp. 585-601
Closed Access | Times Cited: 235
Evaluating urban flood risk using hybrid method of TOPSIS and machine learning
Elham Rafiei-Sardooi, Ali Azareh, Bahram Choubin, et al.
International Journal of Disaster Risk Reduction (2021) Vol. 66, pp. 102614-102614
Open Access | Times Cited: 215
A new approach to flood susceptibility assessment in data-scarce and ungauged regions based on GIS-based hybrid multi criteria decision-making method
Yousef Kanani‐Sadat, Reza Arabsheibani, Farid Karimipour, et al.
Journal of Hydrology (2019) Vol. 572, pp. 17-31
Closed Access | Times Cited: 164
Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran
Khabat Khosravi, Mahdi Panahi, Ali Golkarian, et al.
Journal of Hydrology (2020) Vol. 591, pp. 125552-125552
Closed Access | Times Cited: 162
A novel hybrid of meta-optimization approach for flash flood-susceptibility assessment in a monsoon-dominated watershed, Eastern India
Dipankar Ruidas, Rabin Chakrabortty, Abu Reza Md. Towfiqul Islam, et al.
Environmental Earth Sciences (2022) Vol. 81, Iss. 5
Closed Access | Times Cited: 94
Flood susceptibility mapping using multi-temporal SAR imagery and novel integration of nature-inspired algorithms into support vector regression
Soroosh Mehravar, Seyed Vahid Razavi-Termeh, Armin Moghimi, et al.
Journal of Hydrology (2023) Vol. 617, pp. 129100-129100
Open Access | Times Cited: 78
A Systematic Review of Urban Flood Susceptibility Mapping: Remote Sensing, Machine Learning, and Other Modeling Approaches
Tania Islam, Ethiopia Bisrat Zeleke, Mahmud Afroz, et al.
Remote Sensing (2025) Vol. 17, Iss. 3, pp. 524-524
Open Access | Times Cited: 2
Development of novel hybridized models for urban flood susceptibility mapping
Omid Rahmati, Hamid Darabi, Mahdi Panahi, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 115
Ensemble models of GLM, FDA, MARS, and RF for flood and erosion susceptibility mapping: a priority assessment of sub-basins
Amirhosein Mosavi, Mohammad Golshan, Saeid Janizadeh, et al.
Geocarto International (2020) Vol. 37, Iss. 9, pp. 2541-2560
Closed Access | Times Cited: 113
A Comparative Study of Kernel Logistic Regression, Radial Basis Function Classifier, Multinomial Naïve Bayes, and Logistic Model Tree for Flash Flood Susceptibility Mapping
Binh Thai Pham, Tran Van Phong, Huu Duy Nguyen, et al.
Water (2020) Vol. 12, Iss. 1, pp. 239-239
Open Access | Times Cited: 111
Flood forecasting based on an artificial neural network scheme
Francis Yongwa Dtissibe, Ado Adamou Abba Ari, Chafiq Titouna, et al.
Natural Hazards (2020) Vol. 104, Iss. 2, pp. 1211-1237
Closed Access | Times Cited: 73
Deep Neural Network Utilizing Remote Sensing Datasets for Flood Hazard Susceptibility Mapping in Brisbane, Australia
Bahareh Kalantar, Naonori Ueda, Vahideh Saeidi, et al.
Remote Sensing (2021) Vol. 13, Iss. 13, pp. 2638-2638
Open Access | Times Cited: 73
Machine learning algorithm-based risk assessment of riparian wetlands in Padma River Basin of Northwest Bangladesh
Abu Reza Md. Towfiqul Islam, Swapan Talukdar, Susanta Mahato, et al.
Environmental Science and Pollution Research (2021) Vol. 28, Iss. 26, pp. 34450-34471
Closed Access | Times Cited: 72
Urban Flood-Risk Assessment: Integration of Decision-Making and Machine Learning
Fereshteh Taromideh, Ramin Fazloula, Bahram Choubin, et al.
Sustainability (2022) Vol. 14, Iss. 8, pp. 4483-4483
Open Access | Times Cited: 70
Field based index of flood vulnerability (IFV): A new validation technique for flood susceptible models
Susanta Mahato, Swades Pal, Swapan Talukdar, et al.
Geoscience Frontiers (2021) Vol. 12, Iss. 5, pp. 101175-101175
Open Access | Times Cited: 68
How far spatial resolution affects the ensemble machine learning based flood susceptibility prediction in data sparse region
Tamal Kanti Saha, Swades Pal, Swapan Talukdar, et al.
Journal of Environmental Management (2021) Vol. 297, pp. 113344-113344
Open Access | Times Cited: 59
Flood susceptibility mapping of Northeast coastal districts of Tamil Nadu India using Multi-source Geospatial data and Machine Learning techniques
Subbarayan Saravanan, Devanantham Abijith
Geocarto International (2022) Vol. 37, Iss. 27, pp. 15252-15281
Closed Access | Times Cited: 46
Flood susceptibility mapping using support vector regression and hyper‐parameter optimization
Aryan Salvati, Alireza Moghaddam Nia, Ali Salajegheh, et al.
Journal of Flood Risk Management (2023) Vol. 16, Iss. 4
Open Access | Times Cited: 33
Urban expansion induced loss of natural vegetation cover and ecosystem service values: A scenario-based study in the siliguri municipal corporation (Gateway of North-East India)
Tirthankar Basu, Arijit Das, Ketan Das, et al.
Land Use Policy (2023) Vol. 132, pp. 106838-106838
Closed Access | Times Cited: 33
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
Artificial neural networks for flood susceptibility analysis in Gangarampur sub-division of Dakshin Dinajpur, West Bengal, India
Ankeli Paul
Frontiers in Engineering and Built Environment (2025) Vol. 5, Iss. 1, pp. 1-21
Open Access | Times Cited: 1
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