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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:

Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping
Hossein Shafizadeh‐Moghadam, Roozbeh Valavi, Himan Shahabi, et al.
Journal of Environmental Management (2018) Vol. 217, pp. 1-11
Open Access | Times Cited: 327

Showing 1-25 of 327 citing articles:

A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods
Khabat Khosravi, Himan Shahabi, Binh Thai Pham, et al.
Journal of Hydrology (2019) Vol. 573, pp. 311-323
Closed Access | Times Cited: 562
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
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
Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods
Wei Chen, Yang Li, Weifeng Xue, et al.
The Science of The Total Environment (2019) Vol. 701, pp. 134979-134979
Closed Access | Times Cited: 389
Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method
Farzaneh Sajedi Hosseini, Bahram Choubin, Amir Mosavi, et al.
The Science of The Total Environment (2019) Vol. 711, pp. 135161-135161
Open Access | Times Cited: 304
Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier
Himan Shahabi, Ataollah Shirzadi, Kayvan Ghaderi, et al.
Remote Sensing (2020) Vol. 12, Iss. 2, pp. 266-266
Open Access | Times Cited: 301
Flood susceptibility modelling using novel hybrid approach of reduced-error pruning trees with bagging and random subspace ensembles
Wei Chen, Haoyuan Hong, Shaojun Li, et al.
Journal of Hydrology (2019) Vol. 575, pp. 864-873
Closed Access | Times Cited: 267
GIS-based MCDM – AHP modeling for flood susceptibility mapping of arid areas, southeastern Tunisia
Dhekra Souissi, Lahcen Zouhri, Salma Hammami, et al.
Geocarto International (2019) Vol. 35, Iss. 9, pp. 991-1017
Closed Access | Times Cited: 264
Application of remote sensing and machine learning algorithms for forest fire mapping in a Mediterranean area
Meriame Mohajane, Romulus Costache, Firoozeh Karimi, et al.
Ecological Indicators (2021) Vol. 129, pp. 107869-107869
Open Access | Times Cited: 262
Flood susceptibility mapping using convolutional neural network frameworks
Yi Wang, Zhice Fang, Haoyuan Hong, et al.
Journal of Hydrology (2019) Vol. 582, pp. 124482-124482
Closed Access | Times Cited: 260
Flash flood susceptibility modeling using an optimized fuzzy rule based feature selection technique and tree based ensemble methods
Dieu Tien Bui, Paraskevas Tsangaratos, Phuong Thao Thi Ngo, et al.
The Science of The Total Environment (2019) Vol. 668, pp. 1038-1054
Closed Access | Times Cited: 248
Prediction Success of Machine Learning Methods for Flash Flood Susceptibility Mapping in the Tafresh Watershed, Iran
Saeid Janizadeh, Mohammadtaghi Avand, Abolfazl Jaafari, et al.
Sustainability (2019) Vol. 11, Iss. 19, pp. 5426-5426
Open Access | Times Cited: 234
Flood hazard mapping methods: A review
Rofiat Bunmi Mudashiru, Nuridah Sabtu, Ismail Abustan, et al.
Journal of Hydrology (2021) Vol. 603, pp. 126846-126846
Closed Access | Times Cited: 233
Flash-Flood Susceptibility Assessment Using Multi-Criteria Decision Making and Machine Learning Supported by Remote Sensing and GIS Techniques
Romulus Costache, Quoc Bao Pham, Ehsan Sharifi, et al.
Remote Sensing (2019) Vol. 12, Iss. 1, pp. 106-106
Open Access | Times Cited: 230
Long lead-time daily and monthly streamflow forecasting using machine learning methods
Meiling Cheng, F. Fang, Tsuyoshi Kinouchi, et al.
Journal of Hydrology (2020) Vol. 590, pp. 125376-125376
Closed Access | Times Cited: 230
Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms
Viet‐Ha Nhu, Ataollah Shirzadi, Himan Shahabi, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 8, pp. 2749-2749
Open Access | Times Cited: 221
GIS-based flood hazard mapping using relative frequency ratio method: A case study of Panjkora River Basin, eastern Hindu Kush, Pakistan
Kashif Ullah, Jiquan Zhang
PLoS ONE (2020) Vol. 15, Iss. 3, pp. e0229153-e0229153
Open Access | Times Cited: 216
New Hybrids of ANFIS with Several Optimization Algorithms for Flood Susceptibility Modeling
Dieu Tien Bui, Khabat Khosravi, Shaojun Li, et al.
Water (2018) Vol. 10, Iss. 9, pp. 1210-1210
Open Access | Times Cited: 215
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: 212
A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping
Zhice Fang, Yi Wang, Ling Peng, et al.
International Journal of Geographical Information Science (2020) Vol. 35, Iss. 2, pp. 321-347
Open Access | Times Cited: 211
Predicting flood susceptibility using LSTM neural networks
Zhice Fang, Yi Wang, Ling Peng, et al.
Journal of Hydrology (2020) Vol. 594, pp. 125734-125734
Open Access | Times Cited: 208
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
Geospatial mapping of flood susceptibility and hydro-geomorphic response to the floods in Ulhas basin, India
Sumit Das
Remote Sensing Applications Society and Environment (2019) Vol. 14, pp. 60-74
Closed Access | Times Cited: 196
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 Mapping Using GIS-Based Analytic Network Process: A Case Study of Perlis, Malaysia
Umar Lawal Dano, Abdul‐Lateef Balogun, Abdul-Nasir Matori, et al.
Water (2019) Vol. 11, Iss. 3, pp. 615-615
Open Access | Times Cited: 186
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