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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:

GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, Bagging, and MultiBoost ensemble frameworks
Dieu Tien Bui, Tien-Chung Ho, Biswajeet Pradhan, et al.
Environmental Earth Sciences (2016) Vol. 75, Iss. 14
Closed Access | Times Cited: 291

Showing 1-25 of 291 citing articles:

A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran
Khabat Khosravi, Binh Thai Pham, Kamran Chapi, et al.
The Science of The Total Environment (2018) Vol. 627, pp. 744-755
Closed Access | Times Cited: 653
Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)
Haoyuan Hong, Junzhi Liu, Dieu Tien Bui, et al.
CATENA (2018) Vol. 163, pp. 399-413
Closed Access | Times Cited: 462
Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan
Jie Dou, Ali P. Yunus, Dieu Tien Bui, et al.
Landslides (2019) Vol. 17, Iss. 3, pp. 641-658
Closed Access | Times Cited: 437
Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China
Yi Wang, Zhice Fang, Haoyuan Hong
The Science of The Total Environment (2019) Vol. 666, pp. 975-993
Closed Access | Times Cited: 436
Performance evaluation of the GIS-based data mining techniques of best-first decision tree, random forest, and naïve Bayes tree for landslide susceptibility modeling
Wei Chen, Shuai Zhang, Renwei Li, et al.
The Science of The Total Environment (2018) Vol. 644, pp. 1006-1018
Closed Access | Times Cited: 412
Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China
Wei Chen, Jianbing Peng, Haoyuan Hong, et al.
The Science of The Total Environment (2018) Vol. 626, pp. 1121-1135
Open Access | Times Cited: 404
Landslide spatial modeling: Introducing new ensembles of ANN, MaxEnt, and SVM machine learning techniques
Wei Chen, Hamid Reza Pourghasemi, Aiding Kornejady, et al.
Geoderma (2017) Vol. 305, pp. 314-327
Closed Access | Times Cited: 362
Application of alternating decision tree with AdaBoost and bagging ensembles for landslide susceptibility mapping
Yanli Wu, Yutian Ke, Zhuo Chen, et al.
CATENA (2019) Vol. 187, pp. 104396-104396
Open Access | Times Cited: 347
Mapping landslide susceptibility using data-driven methods
José Luı́s Zêzere, Susana Pereira, Raquel Melo, et al.
The Science of The Total Environment (2017) Vol. 589, pp. 250-267
Closed Access | Times Cited: 299
Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment
Maher Ibrahim Sameen, Biswajeet Pradhan, Saro Lee
CATENA (2019) Vol. 186, pp. 104249-104249
Open Access | Times Cited: 296
GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models
Wei Chen, Hui Li, Enke Hou, et al.
The Science of The Total Environment (2018) Vol. 634, pp. 853-867
Open Access | Times Cited: 292
Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches
Binh Thai Pham, Indra Prakash, Sushant K. Singh, et al.
CATENA (2018) Vol. 175, pp. 203-218
Closed Access | Times Cited: 280
Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping
Zhice Fang, Yi Wang, Ling Peng, et al.
Computers & Geosciences (2020) Vol. 139, pp. 104470-104470
Closed Access | Times Cited: 268
Assessing the predictive capability of ensemble tree methods for landslide susceptibility mapping using XGBoost, gradient boosting machine, and random forest
Emrehan Kutluğ Şahin
SN Applied Sciences (2020) Vol. 2, Iss. 7
Open Access | Times Cited: 258
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
Review on remote sensing methods for landslide detection using machine and deep learning
Amrita Mohan, Amit Kumar Singh, Basant Kumar, et al.
Transactions on Emerging Telecommunications Technologies (2020) Vol. 32, Iss. 7
Closed Access | Times Cited: 238
Meta optimization of an adaptive neuro-fuzzy inference system with grey wolf optimizer and biogeography-based optimization algorithms for spatial prediction of landslide susceptibility
Abolfazl Jaafari, Mahdi Panahi, Binh Thai Pham, et al.
CATENA (2019) Vol. 175, pp. 430-445
Closed Access | Times Cited: 236
Comparative study of landslide susceptibility mapping with different recurrent neural networks
Yi Wang, Zhice Fang, Mao Wang, et al.
Computers & Geosciences (2020) Vol. 138, pp. 104445-104445
Closed Access | Times Cited: 230
Analysis and evaluation of landslide susceptibility: a review on articles published during 2005–2016 (periods of 2005–2012 and 2013–2016)
Hamid Reza Pourghasemi, Zeinab Teimoori Yansari, Panos Panagos, et al.
Arabian Journal of Geosciences (2018) Vol. 11, Iss. 9
Closed Access | Times Cited: 224
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
Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees
Binh Thai Pham, Indra Prakash, Dieu Tien Bui
Geomorphology (2017) Vol. 303, pp. 256-270
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
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
GIS Based Hybrid Computational Approaches for Flash Flood Susceptibility Assessment
Binh Thai Pham, Mohammadtaghi Avand, Saeid Janizadeh, et al.
Water (2020) Vol. 12, Iss. 3, pp. 683-683
Open Access | Times Cited: 206
GIS-based evaluation of landslide susceptibility using hybrid computational intelligence models
Wei Chen, Yang Li
CATENA (2020) Vol. 195, pp. 104777-104777
Closed Access | Times Cited: 204
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