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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:

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

Showing 1-25 of 215 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: 421
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: 385
Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment
Dieu Tien Bui, Paraskevas Tsangaratos, Viet-Tien Nguyen, et al.
CATENA (2020) Vol. 188, pp. 104426-104426
Closed Access | Times Cited: 380
Improving prediction of water quality indices using novel hybrid machine-learning algorithms
Duie Tien Bui, Khabat Khosravi, John P. Tiefenbacher, et al.
The Science of The Total Environment (2020) Vol. 721, pp. 137612-137612
Closed Access | Times Cited: 313
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: 296
Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces
Angela Lausch, Michael E. Schaepman, Andrew K. Skidmore, et al.
Remote Sensing (2020) Vol. 12, Iss. 22, pp. 3690-3690
Open Access | Times Cited: 262
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: 261
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: 243
Flood susceptibility mapping in Dingnan County (China) using adaptive neuro-fuzzy inference system with biogeography based optimization and imperialistic competitive algorithm
Yi Wang, Haoyuan Hong, Wei Chen, et al.
Journal of Environmental Management (2019) Vol. 247, pp. 712-729
Closed Access | Times Cited: 217
Integrated machine learning methods with resampling algorithms for flood susceptibility prediction
Esmaeel Dodangeh, Bahram Choubin, Ahmad Najafi Eigdir, et al.
The Science of The Total Environment (2019) Vol. 705, pp. 135983-135983
Closed Access | Times Cited: 217
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: 217
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: 189
Spatial prediction of groundwater potentiality using ANFIS ensembled with teaching-learning-based and biogeography-based optimization
Wei Chen, Mahdi Panahi, Khabat Khosravi, et al.
Journal of Hydrology (2019) Vol. 572, pp. 435-448
Closed Access | Times Cited: 177
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
Landslide Susceptibility Assessment by Novel Hybrid Machine Learning Algorithms
Binh Thai Pham, Ataollah Shirzadi, Himan Shahabi, et al.
Sustainability (2019) Vol. 11, Iss. 16, pp. 4386-4386
Open Access | Times Cited: 168
Multi-hazard probability assessment and mapping in Iran
Hamid Reza Pourghasemi, Amiya Gayen, Mahdi Panahi, et al.
The Science of The Total Environment (2019) Vol. 692, pp. 556-571
Closed Access | Times Cited: 167
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
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
Spatial Prediction of Landslide Susceptibility Using GIS-Based Data Mining Techniques of ANFIS with Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO)
Wei Chen, Haoyuan Hong, Mahdi Panahi, et al.
Applied Sciences (2019) Vol. 9, Iss. 18, pp. 3755-3755
Open Access | Times Cited: 154
GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms
Alireza Arabameri, Biswajeet Pradhan, Khalil Rezaei, et al.
Journal of Mountain Science (2019) Vol. 16, Iss. 3, pp. 595-618
Closed Access | Times Cited: 148
Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis
Binh Thai Pham, Manh Duc Nguyen, Dong Van Dao, et al.
The Science of The Total Environment (2019) Vol. 679, pp. 172-184
Closed Access | Times Cited: 147
Spatial prediction of flood potential using new ensembles of bivariate statistics and artificial intelligence: A case study at the Putna river catchment of Romania
Romulus Costache, Dieu Tien Bui
The Science of The Total Environment (2019) Vol. 691, pp. 1098-1118
Closed Access | Times Cited: 146
Pathways and challenges of the application of artificial intelligence to geohazards modelling
Abhirup Dikshit, Biswajeet Pradhan, Abdullah Alamri
Gondwana Research (2020) Vol. 100, pp. 290-301
Open Access | Times Cited: 144
Fuzzy-metaheuristic ensembles for spatial assessment of forest fire susceptibility
Hossein Moayedi, Mohammad Mehrabi, Dieu Tien Bui, et al.
Journal of Environmental Management (2020) Vol. 260, pp. 109867-109867
Closed Access | Times Cited: 140
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
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