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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:

Improvement of Best First Decision Trees Using Bagging and Dagging Ensembles for Flood Probability Mapping
Peyman Yariyan, Saeid Janizadeh, Tran Van Phong, et al.
Water Resources Management (2020) Vol. 34, Iss. 9, pp. 3037-3053
Closed Access | Times Cited: 148

Showing 1-25 of 148 citing articles:

Ensemble machine learning paradigms in hydrology: A review
Mohammad Zounemat‐Kermani, Okke Batelaan, Marzieh Fadaee, et al.
Journal of Hydrology (2021) Vol. 598, pp. 126266-126266
Open Access | Times Cited: 440
Flash-flood susceptibility mapping based on XGBoost, random forest and boosted regression trees
Rahebeh Abedi, Romulus Costache, Hossein Shafizadeh‐Moghadam, et al.
Geocarto International (2021) Vol. 37, Iss. 19, pp. 5479-5496
Closed Access | Times Cited: 204
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: 196
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 risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam
Binh Thai Pham, Chinh Luu, Tran Van Phong, et al.
Journal of Hydrology (2020) Vol. 592, pp. 125815-125815
Closed Access | Times Cited: 166
Comprehensive Overview of Flood Modeling Approaches: A Review of Recent Advances
Vijendra Kumar, Kul Vaibhav Sharma, Tommaso Caloiero, et al.
Hydrology (2023) Vol. 10, Iss. 7, pp. 141-141
Open Access | Times Cited: 110
Hydrogeochemical Evaluation of Groundwater Aquifers and Associated Health Hazard Risk Mapping Using Ensemble Data Driven Model in a Water Scares Plateau Region of Eastern India
Dipankar Ruidas, Subodh Chandra Pal, Abu Reza Md. Towfiqul Islam, et al.
Exposure and Health (2022) Vol. 15, Iss. 1, pp. 113-131
Closed Access | Times Cited: 87
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: 52
Enhancing flood susceptibility modeling using multi-temporal SAR images, CHIRPS data, and hybrid machine learning algorithms
Mostafa Riazi, Khabat Khosravi, Kaka Shahedi, et al.
The Science of The Total Environment (2023) Vol. 871, pp. 162066-162066
Closed Access | Times Cited: 51
A GIS-Based Flood Risk Assessment Using the Decision-Making Trial and Evaluation Laboratory Approach at a Regional Scale
Eirini Efraimidou, Mike Spiliotis
Environmental Processes (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 20
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
Flood susceptibility mapping using an improved analytic network process with statistical models
Peyman Yariyan, Mohammadtaghi Avand, Rahim Ali Abbaspour, et al.
Geomatics Natural Hazards and Risk (2020) Vol. 11, Iss. 1, pp. 2282-2314
Open Access | Times Cited: 126
Flood susceptibility mapping and assessment using a novel deep learning model combining multilayer perceptron and autoencoder neural networks
Mohammad Ahmadlou, A’kif Al-Fugara, Abdel Rahman Al‐Shabeeb, et al.
Journal of Flood Risk Management (2020) Vol. 14, Iss. 1
Open Access | Times Cited: 114
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
Estimation of axial load-carrying capacity of concrete-filled steel tubes using surrogate models
Haï-Bang Ly, Binh Thai Pham, Lei Lü, et al.
Neural Computing and Applications (2020) Vol. 33, Iss. 8, pp. 3437-3458
Closed Access | Times Cited: 106
Modeling the fluctuations of groundwater level by employing ensemble deep learning techniques
Haitham Abdulmohsin Afan, Ahmedbahaaaldin Ibrahem Ahmed Osman, Yusuf Essam, et al.
Engineering Applications of Computational Fluid Mechanics (2021) Vol. 15, Iss. 1, pp. 1420-1439
Open Access | Times Cited: 104
Examining LightGBM and CatBoost models for wadi flash flood susceptibility prediction
Mohamed Saber, Tayeb Boulmaiz, Mawloud Guermoui, et al.
Geocarto International (2021) Vol. 37, Iss. 25, pp. 7462-7487
Open Access | Times Cited: 102
Modeling groundwater potential using novel GIS-based machine-learning ensemble techniques
Alireza Arabameri, Subodh Chandra Pal, Fatemeh Rezaie, et al.
Journal of Hydrology Regional Studies (2021) Vol. 36, pp. 100848-100848
Open Access | Times Cited: 97
Comparison of gradient boosted decision trees and random forest for groundwater potential mapping in Dholpur (Rajasthan), India
Shruti Sachdeva, Bijendra Kumar
Stochastic Environmental Research and Risk Assessment (2020) Vol. 35, Iss. 2, pp. 287-306
Open Access | Times Cited: 81
GIS-based spatial modeling of snow avalanches using four novel ensemble models
Peyman Yariyan, Mohammadtaghi Avand, Rahim Ali Abbaspour, et al.
The Science of The Total Environment (2020) Vol. 745, pp. 141008-141008
Closed Access | Times Cited: 78
Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models
Rahim Barzegar, Siamak Razzagh, John Quilty, et al.
Journal of Hydrology (2021) Vol. 598, pp. 126370-126370
Open Access | Times Cited: 75
Comparative Analysis of Artificial Intelligence Models for Accurate Estimation of Groundwater Nitrate Concentration
Shahab S. Band, Saeid Janizadeh, Subodh Chandra Pal, et al.
Sensors (2020) Vol. 20, Iss. 20, pp. 5763-5763
Open Access | Times Cited: 74
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
Application of entropy weighting method for urban flood hazard mapping
Hossein Malekinezhad, Mehdi Sepehri, Quoc Bao Pham, et al.
Acta Geophysica (2021) Vol. 69, Iss. 3, pp. 841-854
Closed Access | Times Cited: 65
Automatic flood detection using sentinel-1 images on the google earth engine
Meysam Moharrami, Mohammad Javanbakht, Sara Attarchi
Environmental Monitoring and Assessment (2021) Vol. 193, Iss. 5
Closed Access | Times Cited: 58
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