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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.

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Showing 26-50 of 450 citing articles:

GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms
Sk Ajim Ali, Farhana Parvin, Jana Vojteková, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 2, pp. 857-876
Open Access | Times Cited: 196
Flood vulnerability mapping using frequency ratio (FR) model: a case study on Kulik river basin, Indo-Bangladesh Barind region
Debabrata Sarkar, Prolay Mondal
Applied Water Science (2019) Vol. 10, Iss. 1
Open Access | Times Cited: 192
Evaluating the application of the statistical index method in flood susceptibility mapping and its comparison with frequency ratio and logistic regression methods
Mahyat Shafapour Tehrany, Lalit Kumar, Mustafa Neamah Jebur, et al.
Geomatics Natural Hazards and Risk (2018) Vol. 10, Iss. 1, pp. 79-101
Open Access | Times Cited: 190
Flash Flood Susceptibility Modeling Using New Approaches of Hybrid and Ensemble Tree-Based Machine Learning Algorithms
Shahab S. Band, Saeid Janizadeh, Subodh Chandra Pal, et al.
Remote Sensing (2020) Vol. 12, Iss. 21, pp. 3568-3568
Open Access | Times Cited: 188
A comparison study of DRASTIC methods with various objective methods for groundwater vulnerability assessment
Khabat Khosravi, Majid Sartaj, Frank T.‐C. Tsai, et al.
The Science of The Total Environment (2018) Vol. 642, pp. 1032-1049
Closed Access | Times Cited: 185
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: 180
Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India
Aman Arora, Alireza Arabameri, Manish Pandey, et al.
The Science of The Total Environment (2020) Vol. 750, pp. 141565-141565
Open Access | Times Cited: 176
Spatial prediction of flood-susceptible areas using frequency ratio and maximum entropy models
Safura Siahkamari, Ali Haghizadeh, Hossein Zeinivand, et al.
Geocarto International (2017) Vol. 33, Iss. 9, pp. 927-941
Closed Access | Times Cited: 175
Geographic information system and AHP-based flood hazard zonation of Vaitarna basin, Maharashtra, India
Sumit Das
Arabian Journal of Geosciences (2018) Vol. 11, Iss. 19
Closed Access | Times Cited: 172
Flood Spatial Modeling in Northern Iran Using Remote Sensing and GIS: A Comparison between Evidential Belief Functions and Its Ensemble with a Multivariate Logistic Regression Model
Duie Tien Bui, Khabat Khosravi, Himan Shahabi, et al.
Remote Sensing (2019) Vol. 11, Iss. 13, pp. 1589-1589
Open Access | Times Cited: 165
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: 161
Application of GIS-based analytic hierarchy process and frequency ratio model to flood vulnerable mapping and risk area estimation at Sundarban region, India
Sk Ajim Ali, Rumana Khatun, Ateeque Ahmad, et al.
Modeling Earth Systems and Environment (2019) Vol. 5, Iss. 3, pp. 1083-1102
Closed Access | Times Cited: 160
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: 159
Assessing flood risk using analytical hierarchy process (AHP) and geographical information system (GIS): application in Coochbehar district of West Bengal, India
Subhankar Chakraborty, Sutapa Mukhopadhyay
Natural Hazards (2019) Vol. 99, Iss. 1, pp. 247-274
Closed Access | Times Cited: 158
Threats of climate and land use change on future flood susceptibility
Paramita Roy, Subodh Chandra Pal, Rabin Chakrabortty, et al.
Journal of Cleaner Production (2020) Vol. 272, pp. 122757-122757
Closed Access | Times Cited: 155
Spatial prediction of landslide susceptibility using hybrid support vector regression (SVR) and the adaptive neuro-fuzzy inference system (ANFIS) with various metaheuristic algorithms
Mahdi Panahi, Amiya Gayen, Hamid Reza Pourghasemi, et al.
The Science of The Total Environment (2020) Vol. 741, pp. 139937-139937
Closed Access | Times Cited: 151
Flood Susceptibility Assessment by Using Bivariate Statistics and Machine Learning Models - A Useful Tool for Flood Risk Management
Romulus Costache
Water Resources Management (2019) Vol. 33, Iss. 9, pp. 3239-3256
Closed Access | Times Cited: 148
Flash flood susceptibility modelling using functional tree and hybrid ensemble techniques
Alireza Arabameri, Sunil Saha, Wei Chen, et al.
Journal of Hydrology (2020) Vol. 587, pp. 125007-125007
Closed Access | Times Cited: 137
Urban waterlogging risk as an undervalued environmental challenge: An Integrated MCDA-GIS based modeling approach
Subham Roy, Arghadeep Bose, Nimai Singha, et al.
Environmental Challenges (2021) Vol. 4, pp. 100194-100194
Open Access | Times Cited: 121
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: 116
Evaluation of multi-hazard map produced using MaxEnt machine learning technique
Narges Javidan, Ataollah Kavian, Hamid Reza Pourghasemi, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 108
Novel ensemble machine learning models in flood susceptibility mapping
Pankaj Prasad, Victor J. Loveson, Bappa Das, et al.
Geocarto International (2021) Vol. 37, Iss. 16, pp. 4571-4593
Closed Access | Times Cited: 104
Flash Flood Susceptibility Assessment and Zonation by Integrating Analytic Hierarchy Process and Frequency Ratio Model with Diverse Spatial Data
Aqil Tariq, Jianguo Yan, Bushra Ghaffar, et al.
Water (2022) Vol. 14, Iss. 19, pp. 3069-3069
Open Access | Times Cited: 69
Application of genetic algorithm in optimization parallel ensemble-based machine learning algorithms to flood susceptibility mapping using radar satellite imagery
Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki, Myoung-Bae Seo, et al.
The Science of The Total Environment (2023) Vol. 873, pp. 162285-162285
Closed Access | Times Cited: 47
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: 47

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