| 1 |
Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning
|
SCIENCE OF THE TOTAL ENVIRONMENT
|
| 2 |
A novel hybrid approach of landslide susceptibility modelling using rotation forest ensemble and different base classifiers
|
Geocarto International
|
| 3 |
Performance Evaluation of Sentinel-2 and Landsat 8 OLI Data for Land Cover/Use Classification Using a Comparison between Machine Learning Algorithms
|
Remote Sensing
|
| 4 |
New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed
|
FORESTS
|
| 5 |
Comparison of Support Vector Machine, Bayesian Logistic Regression, and Alternating Decision Tree Algorithms for Shallow Landslide Susceptibility Mapping along a Mountainous Road in the West of Iran
|
Applied Sciences-Basel
|
| 6 |
Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms
|
International Journal of Environmental Research and Public Health
|
| 7 |
Development of an Artificial Intelligence Approach for Prediction of Consolidation Coefficient of Soft Soil: A Sensitivity Analysis
|
The Open Construction & Building Technology Journal
|
| 8 |
A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods
|
JOURNAL OF HYDROLOGY
|