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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 hybrid optimization method of factor screening predicated on GeoDetector and Random Forest for Landslide Susceptibility Mapping
Deliang Sun, Shuxian Shi, Haijia Wen, et al.
Geomorphology (2021) Vol. 379, pp. 107623-107623
Closed Access | Times Cited: 121

Showing 1-25 of 121 citing articles:

Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization
Xinzhi Zhou, Haijia Wen, Yalan Zhang, et al.
Geoscience Frontiers (2021) Vol. 12, Iss. 5, pp. 101211-101211
Open Access | Times Cited: 288
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: 106
Identifying the essential conditioning factors of landslide susceptibility models under different grid resolutions using hybrid machine learning: A case of Wushan and Wuxi counties, China
Mingyong Liao, Haijia Wen, Ling Yang
CATENA (2022) Vol. 217, pp. 106428-106428
Closed Access | Times Cited: 91
Assessment of landslide susceptibility along mountain highways based on different machine learning algorithms and mapping units by hybrid factors screening and sample optimization
Deliang Sun, Qingyu Gu, Haijia Wen, et al.
Gondwana Research (2022) Vol. 123, pp. 89-106
Closed Access | Times Cited: 87
Landslide susceptibility prediction using artificial neural networks, SVMs and random forest: hyperparameters tuning by genetic optimization algorithm
Mehrdad Daviran, Mehdi Shamekhi, Reza Ghezelbash, et al.
International Journal of Environmental Science and Technology (2022) Vol. 20, Iss. 1, pp. 259-276
Closed Access | Times Cited: 78
An investigation of feature selection methods for soil liquefaction prediction based on tree-based ensemble algorithms using AdaBoost, gradient boosting, and XGBoost
Selçuk Demir, Emrehan Kutluğ Şahin
Neural Computing and Applications (2022) Vol. 35, Iss. 4, pp. 3173-3190
Closed Access | Times Cited: 78
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: 56
Landslide susceptibility prediction considering land use change and human activity: A case study under rapid urban expansion and afforestation in China
Hanxiang Xiong, Chuanming Ma, Minghong Li, et al.
The Science of The Total Environment (2023) Vol. 866, pp. 161430-161430
Closed Access | Times Cited: 52
A LightGBM-based landslide susceptibility model considering the uncertainty of non-landslide samples
Deliang Sun, WU Xiao-qing, Haijia Wen, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 49
Application of genetic algorithm in optimization parallel ensemble-based machine learning algorithms to flood susceptibility mapping using radar satellite imagery
Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki, Myoung-Bae Seo, et al.
The Science of The Total Environment (2023) Vol. 873, pp. 162285-162285
Closed Access | Times Cited: 47
Rapidly assessing earthquake-induced landslide susceptibility on a global scale using random forest
Qian He, Ming Wang, Kai Liu
Geomorphology (2021) Vol. 391, pp. 107889-107889
Closed Access | Times Cited: 81
Application of the Optimal Parameter Geographic Detector Model in the Identification of Influencing Factors of Ecological Quality in Guangzhou, China
Maomao Zhang, Abdulla ‐ Al Kafy, Bing Ren, et al.
Land (2022) Vol. 11, Iss. 8, pp. 1303-1303
Open Access | Times Cited: 65
Improved arithmetic optimization algorithm and its application to carbon fiber reinforced polymer-steel bond strength estimation
Xiaoling Shi, Xinping Yu, Mahzad Esmaeili‐Falak
Composite Structures (2022) Vol. 306, pp. 116599-116599
Closed Access | Times Cited: 61
A hybrid machine learning model for landslide-oriented risk assessment of long-distance pipelines
Haijia Wen, Lei Liu, Jialan Zhang, et al.
Journal of Environmental Management (2023) Vol. 342, pp. 118177-118177
Closed Access | Times Cited: 35
Landslide Susceptibility Mapping Based on Interpretable Machine Learning from the Perspective of Geomorphological Differentiation
Deliang Sun, D C Chen, Jialan Zhang, et al.
Land (2023) Vol. 12, Iss. 5, pp. 1018-1018
Open Access | Times Cited: 34
An interpretable model for landslide susceptibility assessment based on Optuna hyperparameter optimization and Random Forest
Xin Xiao, Yi Zou, Jiangcheng Huang, et al.
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 12
Estimation of PM2.5 Concentration across China Based on Multi-Source Remote Sensing Data and Machine Learning Methods
Yujie Yang, Zhige Wang, Chunxiang Cao, et al.
Remote Sensing (2024) Vol. 16, Iss. 3, pp. 467-467
Open Access | Times Cited: 11
Landslide susceptibility mapping (LSM) based on different boosting and hyperparameter optimization algorithms: A case of Wanzhou District, China
Deliang Sun, Jing Wang, Haijia Wen, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2024) Vol. 16, Iss. 8, pp. 3221-3232
Open Access | Times Cited: 8
The influences of the spatial extent selection for non-landslide samples on statistical-based landslide susceptibility modelling: a case study of Anhui Province in China
Chuhan Wang, Qigen Lin, Leibin Wang, et al.
Natural Hazards (2022) Vol. 112, Iss. 3, pp. 1967-1988
Closed Access | Times Cited: 35
Multi-Scenario Simulation of Production-Living-Ecological Space in the Poyang Lake Area Based on Remote Sensing and RF-Markov-FLUS Model
Huizhong Li, Chaoyang Fang, Yang Xia, et al.
Remote Sensing (2022) Vol. 14, Iss. 12, pp. 2830-2830
Open Access | Times Cited: 33
An input-output-based Bayesian neural network method for analyzing carbon reduction potential: A case study of Guangdong province
Bingyi Zhou, Yongping Li, Y.K. Ding, et al.
Journal of Cleaner Production (2023) Vol. 389, pp. 135986-135986
Closed Access | Times Cited: 21
Examining the Spatially Varying Relationships between Landslide Susceptibility and Conditioning Factors Using a Geographical Random Forest Approach: A Case Study in Liangshan, China
Xiaoliang Dai, Yunqiang Zhu, Kai Sun, et al.
Remote Sensing (2023) Vol. 15, Iss. 6, pp. 1513-1513
Open Access | Times Cited: 20
Prediction of the future landslide susceptibility scenario based on LULC and climate projections
Ankit Tyagi, Reet Kamal Tiwari, Naveen James
Landslides (2023) Vol. 20, Iss. 9, pp. 1837-1852
Closed Access | Times Cited: 17
Landslide susceptibility mapping based on the reliability of landslide and non-landslide sample
Haoyuan Hong, Desheng Wang, A‐Xing Zhu, et al.
Expert Systems with Applications (2023) Vol. 243, pp. 122933-122933
Closed Access | Times Cited: 17
Optimization method of conditioning factors selection and combination for landslide susceptibility prediction
Faming Huang, K Y Liu, Shui‐Hua Jiang, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2024)
Open Access | Times Cited: 7
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