Landslide susceptibility mapping using GIS based multi criteria decision analysis support vector machines and logistic regression

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

1. Assessing the predictive capability of ensemble tree methods for landslide susceptibility mapping using XGBoost, gradient boosting machine, and random forest 2020 Citations 442 · 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. 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
4. Selecting optimal conditioning factors in shallow translational landslide susceptibility mapping using genetic algorithm 2015 Citations 207 · OpenAlex
5. Selecting optimal conditioning factors in shallow translational landslide susceptibility mapping using genetic algorithm 2015 Citations 207 · OpenAlex
6. A comparative study for landslide susceptibility mapping using GIS-based multi-criteria decision analysis (MCDA), logistic regression (LR) and association rule mining (ARM) 2015 Citations 203 · OpenAlex
7. Machine Learning Techniques in Landslide Susceptibility Mapping: A Survey and a Case Study 2018 Citations 184 · OpenAlex
8. Advanced hyperparameter optimization for improved spatial prediction of shallow landslides using extreme gradient boosting (XGBoost) 2022 Citations 180 · OpenAlex
9. Susceptibility mapping of shallow landslides using kernel based Gaussian process support vector machines and logistic regression 2016 Citations 175 · OpenAlex
10. Susceptibility mapping of shallow landslides using kernel-based Gaussian process, support vector machines and logistic regression 2016 Citations 175 · OpenAlex