| 1 |
A novel hybrid approach of landslide susceptibility modelling using rotation forest ensemble and different base classifiers
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Geocarto International
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| 2 |
A hybrid machine learning ensemble approach based on a Radial Basis Function neural network and Rotation Forest for landslide susceptibility modeling: A case study in the Himalayan area, India
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International Journal of Sediment Research
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| 3 |
Development of an Artificial Intelligence Approach for Prediction of Consolidation Coefficient of Soft Soil: A Sensitivity Analysis
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The Open Construction & Building Technology Journal
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| 4 |
Development of a Novel Hybrid Intelligence Approach for Landslide Spatial Prediction
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Applied Sciences-Basel
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| 5 |
Hybrid Machine Learning Approaches for Landslide Susceptibility Modeling
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FORESTS
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| 6 |
A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods
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JOURNAL OF HYDROLOGY
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| 7 |
Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches
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CATENA
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| 8 |
A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran
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SCIENCE OF THE TOTAL ENVIRONMENT
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