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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:

A physics-informed data-driven model for landslide susceptibility assessment in the Three Gorges Reservoir area
Songlin Liu, Luqi Wang, Wengang Zhang, et al.
Geoscience Frontiers (2023) Vol. 14, Iss. 5, pp. 101621-101621
Open Access | Times Cited: 70

Showing 1-25 of 70 citing articles:

Modelling landslide susceptibility prediction: A review and construction of semi-supervised imbalanced theory
Faming Huang, Haowen Xiong, Shui‐Hua Jiang, et al.
Earth-Science Reviews (2024) Vol. 250, pp. 104700-104700
Closed Access | Times Cited: 61
Predicting the hydraulic response of critical transport infrastructures during extreme flood events
Seyed Mehran Ahmadi, Saeed Balahang, Soroush Abolfathi
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108573-108573
Open Access | Times Cited: 45
Refined and dynamic susceptibility assessment of landslides using InSAR and machine learning models
Yingdong Wei, Haijun Qiu, Zijing Liu, et al.
Geoscience Frontiers (2024) Vol. 15, Iss. 6, pp. 101890-101890
Open Access | Times Cited: 44
Physics-informed optimization for a data-driven approach in landslide susceptibility evaluation
Songlin Liu, Luqi Wang, Wengang Zhang, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2024) Vol. 16, Iss. 8, pp. 3192-3205
Open Access | Times Cited: 29
Improving pixel-based regional landslide susceptibility mapping
Xin Wei, Paolo Gardoni, Lulu Zhang, et al.
Geoscience Frontiers (2024) Vol. 15, Iss. 4, pp. 101782-101782
Open Access | Times Cited: 21
Uncertainties in landslide susceptibility prediction modeling: A review on the incompleteness of landslide inventory and its influence rules
Faming Huang, Daxiong Mao, Shui‐Hua Jiang, et al.
Geoscience Frontiers (2024) Vol. 15, Iss. 6, pp. 101886-101886
Open Access | Times Cited: 19
PSLSA v2.0: An automatic Python package integrating machine learning models for regional landslide susceptibility assessment
Zizheng Guo, Haojie Wang, Jun He, et al.
Environmental Modelling & Software (2025) Vol. 186, pp. 106367-106367
Closed Access | Times Cited: 5
Soft computing for determining base resistance of super-long piles in soft soil: A coupled SPBO-XGBoost approach
Tan Nguyen, Duy-Khuong Ly, Quoc Thien Huynh, et al.
Computers and Geotechnics (2023) Vol. 162, pp. 105707-105707
Closed Access | Times Cited: 35
Estimating Axial Bearing Capacity of Driven Piles Using Tuned Random Forest Frameworks
Belal Mohammadi Yaychi, Mahzad Esmaeili‐Falak
Geotechnical and Geological Engineering (2024)
Closed Access | Times Cited: 17
Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm
Hongzhi Cui, Jian Ji, Marcel Hürlimann, et al.
Landslides (2024) Vol. 21, Iss. 6, pp. 1461-1481
Closed Access | Times Cited: 16
Application and interpretability of ensemble learning for landslide susceptibility mapping along the Three Gorges Reservoir area, China
Bo Liu, Haixiang Guo, Jinling Li, et al.
Natural Hazards (2024) Vol. 120, Iss. 5, pp. 4601-4632
Closed Access | Times Cited: 15
Interferometric Synthetic Aperture Radar (InSAR)-Based Absence Sampling for Machine-Learning-Based Landslide Susceptibility Mapping: The Three Gorges Reservoir Area, China
Ruiqi Zhang, Lele Zhang, Zhice Fang, et al.
Remote Sensing (2024) Vol. 16, Iss. 13, pp. 2394-2394
Open Access | Times Cited: 11
Interpretable machine learning models and decision-making mechanisms for landslide hazard assessment under different rainfall conditions
Haijia Wen, Fangyi Yan, Junhao Huang, et al.
Expert Systems with Applications (2025), pp. 126582-126582
Closed Access | Times Cited: 1
Synergistic evolution of hydrological and movement characteristics of Majiagou landslide and identification of key triggering factors through interpretable machine learning
Wenmin Yao, Xin Zhang, Changdong Li, et al.
Bulletin of Engineering Geology and the Environment (2025) Vol. 84, Iss. 2
Closed Access | Times Cited: 1
A graph deep learning method for landslide displacement prediction based on global navigation satellite system positioning
Chuan Yang, Yue Yin, Jiantong Zhang, et al.
Geoscience Frontiers (2023) Vol. 15, Iss. 1, pp. 101690-101690
Open Access | Times Cited: 22
A comparative study of regional landslide susceptibility mapping with multiple machine learning models
Yunhao Wang, Luqi Wang, Songlin Liu, et al.
Geological Journal (2023) Vol. 59, Iss. 9, pp. 2383-2400
Closed Access | Times Cited: 19
Single landslide risk assessment considering rainfall‐induced landslide hazard and the vulnerability of disaster‐bearing body
Faming Huang, K Y Liu, Zhiyong Li, et al.
Geological Journal (2024) Vol. 59, Iss. 9, pp. 2549-2565
Closed Access | Times Cited: 8
Application of Soft Computing Techniques for Slope Stability Analysis
Rashid Mustafa, Akash Kumar, Sonu Kumar, et al.
Transportation Infrastructure Geotechnology (2024) Vol. 11, Iss. 6, pp. 3903-3940
Closed Access | Times Cited: 8
A physics-informed machine learning solution for landslide susceptibility mapping based on three-dimensional slope stability evaluation
Yunhao Wang, Luqi Wang, Wengang Zhang, et al.
Journal of Central South University (2024)
Closed Access | Times Cited: 8
Landslide susceptibility mapping using physics-guided machine learning: a case study of a debris flow event in Colorado Front Range
Te Pei, Tong Qiu
Acta Geotechnica (2024) Vol. 19, Iss. 10, pp. 6617-6641
Closed Access | Times Cited: 8
Bayesian ensemble learning and Shapley additive explanations for fast estimation of slope stability with a physics-informed database
Dongze Lei, Junwei Ma, Guangcheng Zhang, et al.
Natural Hazards (2024)
Closed Access | Times Cited: 8
Impact of sampling for landslide susceptibility assessment using interpretable machine learning models
Bin Wu, Zhenming Shi, Hongchao Zheng, et al.
Bulletin of Engineering Geology and the Environment (2024) Vol. 83, Iss. 11
Closed Access | Times Cited: 8
Application of percentile color intensities of borehole images for automatic fluorite grade assessment
Enming Li, Pablo Segarra, José A. Sanchidrián, et al.
Ore Geology Reviews (2023) Vol. 163, pp. 105790-105790
Open Access | Times Cited: 14
Physics-informed and data-driven machine learning of rock mass classification using prior geological knowledge and TBM operational data
Chenhao Zhang, Yu Wang, Lei-jie Wu, et al.
Tunnelling and Underground Space Technology (2024) Vol. 152, pp. 105923-105923
Closed Access | Times Cited: 6
Determination of alternative forest road routes using produced landslide susceptibility maps: A case study of Tonya (Trabzon), Türkiye
Fatih Kadı, Osman Salih Yılmaz
International Journal of Engineering and Geosciences (2024) Vol. 9, Iss. 2, pp. 147-164
Open Access | Times Cited: 5
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