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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:

Bagging-based machine learning algorithms for landslide susceptibility modeling
Tingyu Zhang, Quan Fu, Hao Wang, et al.
Natural Hazards (2021) Vol. 110, Iss. 2, pp. 823-846
Open Access | Times Cited: 47

Showing 1-25 of 47 citing articles:

Landslide Susceptibility Mapping Using Machine Learning: A Literature Survey
Moziihrii Ado, Khwairakpam Amitab, Arnab Kumar Maji, et al.
Remote Sensing (2022) Vol. 14, Iss. 13, pp. 3029-3029
Open Access | Times Cited: 104
Landslide Susceptibility mapping using random forest and extreme gradient boosting: A case study of Fengjie, Chongqing
Wengang Zhang, Yuwei He, Luqi Wang, et al.
Geological Journal (2023) Vol. 58, Iss. 6, pp. 2372-2387
Closed Access | Times Cited: 80
Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy
Taorui Zeng, Liyang Wu, Dario Peduto, et al.
Geoscience Frontiers (2023) Vol. 14, Iss. 6, pp. 101645-101645
Open Access | Times Cited: 76
Daily River flow Simulation Using Ensemble Disjoint Aggregating M5-Prime Model
Khabat Khosravi, Nasrin Fathollahzadeh Attar, Sayed M. Bateni, et al.
Heliyon (2024) Vol. 10, Iss. 20, pp. e37965-e37965
Open Access | Times Cited: 17
Multi-objective robust optimization of reservoir operation for real-time flood control under forecasting uncertainty
Xinting Yu, Yue‐Ping Xu, Haiting Gu, et al.
Journal of Hydrology (2023) Vol. 620, pp. 129421-129421
Closed Access | Times Cited: 24
LCFSTE: Landslide Conditioning Factors and Swin Transformer Ensemble for Landslide Susceptibility Assessment
Tao Chen, Qingye Wang, Zeyang Zhao, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024) Vol. 17, pp. 6444-6454
Open Access | Times Cited: 12
Hybridizing genetic random forest and self-attention based CNN-LSTM algorithms for landslide susceptibility mapping in Darjiling and Kurseong, India
Armin Moghimi, Chiranjit Singha, Mahdiyeh Fathi, et al.
Quaternary Science Advances (2024) Vol. 14, pp. 100187-100187
Open Access | Times Cited: 10
Comparison of tree-based ensemble learning algorithms for landslide susceptibility mapping in Murgul (Artvin), Turkey
Ziya Usta, Halil Akıncı, Alper Tunga Akın
Earth Science Informatics (2024) Vol. 17, Iss. 2, pp. 1459-1481
Open Access | Times Cited: 9
Refined landslide susceptibility mapping in township area using ensemble machine learning method under dataset replenishment strategy
Fancheng Zhao, Fasheng Miao, Yiping Wu, et al.
Gondwana Research (2024) Vol. 131, pp. 20-37
Closed Access | Times Cited: 9
Application of Bagging, Boosting and Stacking Ensemble and EasyEnsemble Methods for Landslide Susceptibility Mapping in the Three Gorges Reservoir Area of China
Xueling Wu, Junyang Wang
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 6, pp. 4977-4977
Open Access | Times Cited: 16
Spatial Prediction of Landslide Susceptibility Using Logistic Regression (LR), Functional Trees (FTs), and Random Subspace Functional Trees (RSFTs) for Pengyang County, China
Hui Shang, Lixiang Su, Wei Chen, et al.
Remote Sensing (2023) Vol. 15, Iss. 20, pp. 4952-4952
Open Access | Times Cited: 16
A frequency ratio–based sampling strategy for landslide susceptibility assessment
Leilei Liu, Yili Zhang, Ting Xiao, et al.
Bulletin of Engineering Geology and the Environment (2022) Vol. 81, Iss. 9
Closed Access | Times Cited: 24
Deep learning to assess the effects of land use/land cover and climate change on landslide susceptibility in the Tra Khuc river basin of Vietnam
Quan Vu Viet Du, Huu Duy Nguyen, Viet Thanh Pham, et al.
Geocarto International (2023) Vol. 38, Iss. 1
Open Access | Times Cited: 15
Application of GIS-based data-driven bivariate statistical models for landslide prediction: a case study of highly affected landslide prone areas of Teesta River basin
Indrajit Poddar, Ranjan Roy
Quaternary Science Advances (2023) Vol. 13, pp. 100150-100150
Open Access | Times Cited: 15
SADXAI: Predicting social anxiety disorder using multiple interpretable artificial intelligence techniques
Krishnaraj Chadaga, Srikanth Prabhu, Niranjana Sampathila, et al.
SLAS TECHNOLOGY (2024) Vol. 29, Iss. 2, pp. 100129-100129
Open Access | Times Cited: 4
Advanced and hybrid machine learning techniques for predicting compressive strength in palm oil fuel ash-modified concrete with SHAP analysis
Tariq Ali, Kennedy C. Onyelowe, Muhammad Sarmad Mahmood, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Machine Learning-assisted Investigation of Landslide Susceptibility for Aglar Watershed in the Lesser Himalaya Region
Dipika Keshri, Shovan Lal Chattoraj, Rakesh Kumar Pandey, et al.
Journal of the Geological Society of India (2025) Vol. 101, Iss. 3, pp. 384-396
Closed Access
Machine learning models for estimating the compressive strength of rubberized concrete subjected to elevated temperature: Optimization and hyper-tuning
Turki S. Alahmari, Irfan Ullah, Furqan Farooq
Sustainable Chemistry and Pharmacy (2024) Vol. 42, pp. 101763-101763
Closed Access | Times Cited: 4
Towards improving decision tree induction by combining split evaluation measures
Octavio Loyola‐González, Ernesto Ramírez-Sáyago, Miguel Angel Medina‐Pérez
Knowledge-Based Systems (2023) Vol. 277, pp. 110832-110832
Closed Access | Times Cited: 10
Multi‐hazard assessment using machine learning and remote sensing in the North Central region of Vietnam
Huu Duy Nguyen, Dinh Kha Dang, Quang‐Thanh Bui, et al.
Transactions in GIS (2023) Vol. 27, Iss. 5, pp. 1614-1640
Closed Access | Times Cited: 9
Explainable AI: Machine Learning Interpretation in Blackcurrant Powders
Krzysztof Przybył
Sensors (2024) Vol. 24, Iss. 10, pp. 3198-3198
Open Access | Times Cited: 3
Developing a new method for future groundwater potentiality mapping under climate change in Bisha watershed, Saudi Arabia
Javed Mallick, Mohammed K. Al Mesfer, Majed Alsubih, et al.
Geocarto International (2022) Vol. 37, Iss. 26, pp. 14495-14527
Closed Access | Times Cited: 12
Analysis of land use/land cover change (LULCC) and debris flow risks in Adama district, Ethiopia, aided by numerical simulation and deep learning-based remote sensing
Amanuel Kumsa Bojer, Muhammed Edris Ahmed, Desta Jula Bekalo, et al.
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 12, pp. 4893-4910
Open Access | Times Cited: 7
Landslide susceptibility prediction using machine learning and remote sensing: Case study in Thua Thien Hue province, Vietnam
Huu Duy Nguyen, Quoc Huy Nguyen, Quan Vu Viet Du, et al.
Geological Journal (2023) Vol. 59, Iss. 2, pp. 636-658
Open Access | Times Cited: 7
Designing high elastic modulus magnesium-based composite materials via machine learning approach
Zhu Zhi-hong, Wenhang Ning, Xuanyang Niu, et al.
Materials Today Communications (2023) Vol. 37, pp. 107249-107249
Open Access | Times Cited: 7
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