Landslide susceptibility assessment of Uttarakhand area of India has been done by applying five machine learning methods namely Support Vector Machines (SVM), ...
A Comparative Study of Different Machine Learning Methods for Landslide Susceptibility Assessment: A Case Study of Uttarakhand Area (India). July 2016 ...
Landslide susceptibility assessment of Uttarakhand area of India has been done by applying five machine learning methods namely Support Vector Machines (SVM) ...
Landslide susceptibility assessment of Uttarakhand area of India has been done by applying five machine learning methods namely Support Vector Machines ...
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A comparative study of different machine learning methods for landslide susceptibility assessment: A case study of Uttarakhand area (India) · Environmental ...
Application and comparison of decision tree-based machine learning methods in landside susceptibility assessment at pauri garhwal area, uttarakhand, India.
In the present study, four linear and nonlinear machine learning algorithms were selected to develop landslide susceptibility maps: MaxEnt, SVM, ANN and RF.
The objective of this study is to make a comparison of the prediction performance of three techniques, Functional Trees (FT), Multilayer Perceptron Neural ...
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A comparative study of different machine learning models for landslide susceptibility prediction: a case study of Kullu-to-Rohtang pass transport corridor, ...
Nov 22, 2022 · In this paper, the prediction accuracy of five hybrid models for landslide occurrence in the Uttarkashi, Uttarakhand (India) was evaluated and compared.