Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping
Binh Thai Pham, T. Nguyen‐Thoi, Chongchong Qi, et al.
CATENA (2020) Vol. 195, pp. 104805-104805
Closed Access | Times Cited: 136

Showing 1-25 of 136 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: 303
Predictive Performances of Ensemble Machine Learning Algorithms in Landslide Susceptibility Mapping Using Random Forest, Extreme Gradient Boosting (XGBoost) and Natural Gradient Boosting (NGBoost)
Taşkın Kavzoǧlu, Alihan Teke
Arabian Journal for Science and Engineering (2022) Vol. 47, Iss. 6, pp. 7367-7385
Closed Access | Times Cited: 198
A hybrid ensemble-based deep-learning framework for landslide susceptibility mapping
Liang Lv, Tao Chen, Jie Dou, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 108, pp. 102713-102713
Open Access | Times Cited: 119
An interpretable model for the susceptibility of rainfall-induced shallow landslides based on SHAP and XGBoost
Xinzhi Zhou, Haijia Wen, Ziwei Li, et al.
Geocarto International (2022) Vol. 37, Iss. 26, pp. 13419-13450
Closed Access | Times Cited: 114
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: 109
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: 84
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
Predicting and Analyzing Road Traffic Injury Severity Using Boosting-Based Ensemble Learning Models with SHAPley Additive exPlanations
Sheng Dong, Afaq Khattak, Irfan Ullah, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 5, pp. 2925-2925
Open Access | Times Cited: 72
Enhancing flood susceptibility modeling using multi-temporal SAR images, CHIRPS data, and hybrid machine learning algorithms
Mostafa Riazi, Khabat Khosravi, Kaka Shahedi, et al.
The Science of The Total Environment (2023) Vol. 871, pp. 162066-162066
Closed Access | Times Cited: 51
An identification method of potential landslide zones using InSAR data and landslide susceptibility
Yi He, Wenhui Wang, Lifeng Zhang, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 44
Effects of non-landslide sampling strategies on machine learning models in landslide susceptibility mapping
Tengfei Gu, Ping Duan, Mingguo Wang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 23
Integrating Machine Learning Ensembles for Landslide Susceptibility Mapping in Northern Pakistan
Nafees Ali, Jian Chen, Xiaodong Fu, et al.
Remote Sensing (2024) Vol. 16, Iss. 6, pp. 988-988
Open Access | Times Cited: 17
Multi-Hazard Exposure Mapping Using Machine Learning for the State of Salzburg, Austria
Thimmaiah Gudiyangada Nachappa, Omid Ghorbanzadeh, Khalil Gholamnia, et al.
Remote Sensing (2020) Vol. 12, Iss. 17, pp. 2757-2757
Open Access | Times Cited: 80
Prediction of spatiotemporal stability and rainfall threshold of shallow landslides using the TRIGRS and Scoops3D models
Jianyin He, Haijun Qiu, Feihang Qu, et al.
CATENA (2020) Vol. 197, pp. 104999-104999
Closed Access | Times Cited: 77
Landslide and Wildfire Susceptibility Assessment in Southeast Asia Using Ensemble Machine Learning Methods
Qian He, Ziyu Jiang, Ming Wang, et al.
Remote Sensing (2021) Vol. 13, Iss. 8, pp. 1572-1572
Open Access | Times Cited: 64
Artificial neural network approaches for disaster management: A literature review
Sreeparna Guha, Rabin K. Jana, Manas Kumar Sanyal
International Journal of Disaster Risk Reduction (2022) Vol. 81, pp. 103276-103276
Closed Access | Times Cited: 57
Classification of earthquakes, explosions and mining-induced earthquakes based on XGBoost algorithm
Tingting Wang, Yinju Bian, Yixiao Zhang, et al.
Computers & Geosciences (2022) Vol. 170, pp. 105242-105242
Open Access | Times Cited: 52
Tempo-Spatial Landslide Susceptibility Assessment from the Perspective of Human Engineering Activity
Taorui Zeng, Zizheng Guo, Linfeng Wang, et al.
Remote Sensing (2023) Vol. 15, Iss. 16, pp. 4111-4111
Open Access | Times Cited: 29
Application of index of entropy and Geospatial techniques for landslide prediction in Lunglei district, Mizoram, India
Jonmenjoy Barman, Syed Sadath Ali, Brototi Biswas, et al.
Natural Hazards Research (2023) Vol. 3, Iss. 3, pp. 508-521
Open Access | Times Cited: 28
Machine learning based landslide susceptibility mapping models and GB-SAR based landslide deformation monitoring systems: Growth and evolution
Babitha Ganesh, Shweta Vincent, Sameena Pathan, et al.
Remote Sensing Applications Society and Environment (2023) Vol. 29, pp. 100905-100905
Closed Access | Times Cited: 26
Prolonged influence of urbanization on landslide susceptibility
Tyler Rohan, Eitan Shelef, Benjamin B. Mirus, et al.
Landslides (2023) Vol. 20, Iss. 7, pp. 1433-1447
Closed Access | Times Cited: 25
Exploring the spatial patterns of landslide susceptibility assessment using interpretable Shapley method: Mechanisms of landslide formation in the Sichuan-Tibet region
Jichao Lv, Rui Zhang, Age Shama, et al.
Journal of Environmental Management (2024) Vol. 366, pp. 121921-121921
Closed Access | Times Cited: 12
A SHAP-Enhanced XGBoost Model for Interpretable Prediction of Coseismic Landslides
Haijia Wen, Bo Liu, Mingrui Di, et al.
Advances in Space Research (2024) Vol. 74, Iss. 8, pp. 3826-3854
Closed Access | Times Cited: 9
Geotourism site suitability assessment by a novel GIS-based MCDM method in the Eastern Duars region (Himalayan foothill) of West Bengal, India
Nazrul Islam, Indrayudh Paul, Bappa Sarkar
Environment Development and Sustainability (2025)
Closed Access | Times Cited: 1
GIS-Based Comparative Study of the Bayesian Network, Decision Table, Radial Basis Function Network and Stochastic Gradient Descent for the Spatial Prediction of Landslide Susceptibility
Junpeng Huang, Sixiang Ling, Xiyong Wu, et al.
Land (2022) Vol. 11, Iss. 3, pp. 436-436
Open Access | Times Cited: 36
Page 1 - Next Page

Scroll to top