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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:

Bagging based Support Vector Machines for spatial prediction of landslides
Binh Thai Pham, Dieu Tien Bui, Indra Prakash
Environmental Earth Sciences (2018) Vol. 77, Iss. 4
Closed Access | Times Cited: 132

Showing 1-25 of 132 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
Landslide spatial modelling using novel bivariate statistical based Naïve Bayes, RBF Classifier, and RBF Network machine learning algorithms
Qingfeng He, Himan Shahabi, Ataollah Shirzadi, et al.
The Science of The Total Environment (2019) Vol. 663, pp. 1-15
Closed Access | Times Cited: 220
A novel hybrid intelligent model of support vector machines and the MultiBoost ensemble for landslide susceptibility modeling
Binh Thai Pham, Abolfazl Jaafari, Indra Prakash, et al.
Bulletin of Engineering Geology and the Environment (2018) Vol. 78, Iss. 4, pp. 2865-2886
Closed Access | Times Cited: 219
Machine learning ensemble modelling as a tool to improve landslide susceptibility mapping reliability
Mariano Di Napoli, Francesco Carotenuto, Andrea Cevasco, et al.
Landslides (2020) Vol. 17, Iss. 8, pp. 1897-1914
Closed Access | Times Cited: 208
Prediction of shear strength of soft soil using machine learning methods
Binh Thai Pham, Lê Hoàng Sơn, Tuan-Anh Hoang, et al.
CATENA (2018) Vol. 166, pp. 181-191
Closed Access | Times Cited: 204
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: 204
Application of artificial intelligence in geotechnical engineering: A state-of-the-art review
Abolfazl Baghbani, Tanveer Choudhury, Susanga Costa, et al.
Earth-Science Reviews (2022) Vol. 228, pp. 103991-103991
Closed Access | Times Cited: 199
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: 188
Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping
Ataollah Shirzadi, Karim Soliamani, Mahmood Habibnejhad, et al.
Sensors (2018) Vol. 18, Iss. 11, pp. 3777-3777
Open Access | Times Cited: 181
A novel ensemble modeling approach for the spatial prediction of tropical forest fire susceptibility using LogitBoost machine learning classifier and multi-source geospatial data
Mahyat Shafapour Tehrany, Simon Jones, Farzin Shabani, et al.
Theoretical and Applied Climatology (2018) Vol. 137, Iss. 1-2, pp. 637-653
Closed Access | Times Cited: 173
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
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
Effectiveness assessment of Keras based deep learning with different robust optimization algorithms for shallow landslide susceptibility mapping at tropical area
Viet‐Ha Nhu, Nhat‐Duc Hoang, Hieu Nguyen, et al.
CATENA (2020) Vol. 188, pp. 104458-104458
Closed Access | Times Cited: 140
Landslide Susceptibility Assessment at Mila Basin (Algeria): A Comparative Assessment of Prediction Capability of Advanced Machine Learning Methods
Abdelaziz Merghadi, Abderrahmane Boumezbeur, Dieu Tien Bui
ISPRS International Journal of Geo-Information (2018) Vol. 7, Iss. 7, pp. 268-268
Open Access | Times Cited: 154
A novel hybrid approach of Bayesian Logistic Regression and its ensembles for landslide susceptibility assessment
Mousa Abedini, Bahareh Ghasemian, Ataollah Shirzadi, et al.
Geocarto International (2018) Vol. 34, Iss. 13, pp. 1427-1457
Closed Access | Times Cited: 131
Optimization of Computational Intelligence Models for Landslide Susceptibility Evaluation
Xia Zhao, Wei Chen
Remote Sensing (2020) Vol. 12, Iss. 14, pp. 2180-2180
Open Access | Times Cited: 128
A similarity-based approach to sampling absence data for landslide susceptibility mapping using data-driven methods
A‐Xing Zhu, Miao Yamin, Junzhi Liu, et al.
CATENA (2019) Vol. 183, pp. 104188-104188
Closed Access | Times Cited: 126
Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment
Viet‐Ha Nhu, Ayub Mohammadi, Himan Shahabi, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 14, pp. 4933-4933
Open Access | Times Cited: 121
New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed
Dieu Tien Bui, Ataollah Shirzadi, Himan Shahabi, et al.
Forests (2019) Vol. 10, Iss. 9, pp. 743-743
Open Access | Times Cited: 118
Modeling and Uncertainty Analysis of Groundwater Level Using Six Evolutionary Optimization Algorithms Hybridized with ANFIS, SVM, and ANN
Akram Seifi, Mohammad Ehteram, Vijay P. Singh, et al.
Sustainability (2020) Vol. 12, Iss. 10, pp. 4023-4023
Open Access | Times Cited: 108
A comparison of Support Vector Machines and Bayesian algorithms for landslide susceptibility modelling
Binh Thai Pham, Indra Prakash, Khabat Khosravi, et al.
Geocarto International (2018) Vol. 34, Iss. 13, pp. 1385-1407
Closed Access | Times Cited: 107
Enhancing Prediction Performance of Landslide Susceptibility Model Using Hybrid Machine Learning Approach of Bagging Ensemble and Logistic Model Tree
Xuan Luan Truong, Muneki Mitamura, Yasuyuki Kono, et al.
Applied Sciences (2018) Vol. 8, Iss. 7, pp. 1046-1046
Open Access | Times Cited: 100
A Novel Integrated Approach of Relevance Vector Machine Optimized by Imperialist Competitive Algorithm for Spatial Modeling of Shallow Landslides
Dieu Tien Bui, Himan Shahabi, Ataollah Shirzadi, et al.
Remote Sensing (2018) Vol. 10, Iss. 10, pp. 1538-1538
Open Access | Times Cited: 99
GIS-based spatial prediction of tropical forest fire danger using a new hybrid machine learning method
Dieu Tien Bui, Van Hung Le, Nhat‐Duc Hoang
Ecological Informatics (2018) Vol. 48, pp. 104-116
Open Access | Times Cited: 96
Urban waterlogging susceptibility assessment based on a PSO-SVM method using a novel repeatedly random sampling idea to select negative samples
Xianzhe Tang, Haoyuan Hong, Yuqin Shu, et al.
Journal of Hydrology (2019) Vol. 576, pp. 583-595
Closed Access | Times Cited: 93
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