Susceptibility mapping of shallow landslides using kernel-based Gaussian process, support vector machines and logistic regression

42 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).

1. Predictive Performances of Ensemble Machine Learning Algorithms in Landslide Susceptibility Mapping Using Random Forest, Extreme Gradient Boosting (XGBoost) and Natural Gradient Boosting (NGBoost) 2022 Citations 367 · OpenAlex
2. Predictive Performances of Ensemble Machine Learning Algorithms in Landslide Susceptibility Mapping Using Random Forest, Extreme Gradient Boosting (XGBoost) and Natural Gradient Boosting (NGBoost) 2022 Citations 367 · OpenAlex
3. Machine Learning Techniques in Landslide Susceptibility Mapping: A Survey and a Case Study 2018 Citations 184 · OpenAlex
4. Advanced hyperparameter optimization for improved spatial prediction of shallow landslides using extreme gradient boosting (XGBoost) 2022 Citations 180 · OpenAlex
5. A comparative assessment of canonical correlation forest, random forest, rotation forest and logistic regression methods for landslide susceptibility mapping 2020 Citations 152 · OpenAlex
6. A comparative assessment of canonical correlation forest, random forest, rotation forest and logistic regression methods for landslide susceptibility mapping 2018 Citations 152 · OpenAlex
7. Comparing classical statistic and machine learning models in landslide susceptibility mapping in Ardanuc (Artvin), Turkey 2021 Citations 96 · OpenAlex
8. Comparing classical statistic and machine learning models in landslide susceptibility mapping in Ardanuc (Artvin), Turkey 2021 Citations 96 · OpenAlex
9. Random Forest-Based Landslide Susceptibility Mapping in Coastal Regions of Artvin, Turkey 2020 Citations 90 · OpenAlex
10. Assessing and mapping landslide susceptibility using different machine learning methods 2022 Citations 69 · OpenAlex