Modelling landslide susceptibility prediction: a review and construction of semi-supervised imbalanced theory
F Huang, H **/links/62541c01ef013420666a60a7/Comparisons-of-heuristic-general-statistical-and-machine-learning-models-for-landslide-susceptibility-prediction-and-map**.pdf" data-clk="hl=ro&sa=T&oi=gga&ct=gga&cd=2&d=4629949251791971158&ei=LzHHZ5X7OMSPieoPg8jg0A0" data-clk-atid="VmMlYVDiQEAJ" target="_blank">[PDF] researchgate.net
Comparisons of heuristic, general statistical and machine learning models for landslide susceptibility prediction and map**
Commonly used data-driven models for landslide susceptibility prediction (LSP) can be
mainly classified as heuristic, general statistical or machine learning models. This study …
mainly classified as heuristic, general statistical or machine learning models. This study …
Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment
DT Bui, P Tsangaratos, VT Nguyen, N Van Liem… - Catena, 2020 - Elsevier
The main objective of the current study was to introduce a Deep Learning Neural Network
(DLNN) model in landslide susceptibility assessments and compare its predictive …
(DLNN) model in landslide susceptibility assessments and compare its predictive …
GIS-based comparative assessment of flood susceptibility map** using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and …
Flood is a devastating natural hazard that may cause damage to the environment
infrastructure, and society. Hence, identifying the susceptible areas to flood is an important …
infrastructure, and society. Hence, identifying the susceptible areas to flood is an important …
Comparison of convolutional neural networks for landslide susceptibility map** in Yanshan County, China
Assessments of landslide disasters are becoming increasingly urgent. The aim of this study
is to investigate a convolutional neural network (CNN) framework for landslide susceptibility …
is to investigate a convolutional neural network (CNN) framework for landslide susceptibility …
[HTML][HTML] Uncertainty pattern in landslide susceptibility prediction modelling: Effects of different landslide boundaries and spatial shape expressions
In some studies on landslide susceptibility map** (LSM), landslide boundary and spatial
shape characteristics have been expressed in the form of points or circles in the landslide …
shape characteristics have been expressed in the form of points or circles in the landslide …
A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility map**
This study introduces four heterogeneous ensemble-learning techniques, that is, stacking,
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …