[HTML][HTML] Geomorphometry and terrain analysis: Data, methods, platforms and applications
Terrain is considered one of the most essential natural geographic features and is a key
factor in physical processes. Geomorphometry and terrain analyses have provided a wealth …
factor in physical processes. Geomorphometry and terrain analyses have provided a wealth …
[HTML][HTML] Machine learning for landslides prevention: a survey
Landslides are one of the most critical categories of natural disasters worldwide and induce
severely destructive outcomes to human life and the overall economic system. To reduce its …
severely destructive outcomes to human life and the overall economic system. To reduce its …
Comparisons of heuristic, general statistical and machine learning models for landslide susceptibility prediction and mapping
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 …
Comparison of convolutional neural networks for landslide susceptibility mapping 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 …
GIS-based comparative assessment of flood susceptibility mapping 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 …
[HTML][HTML] GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms
Hazards and disasters have always negative impacts on the way of life. Landslide is an
overwhelming natural as well as man-made disaster that causes loss of natural resources …
overwhelming natural as well as man-made disaster that causes loss of natural resources …
A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping
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 …
[HTML][HTML] Improved prediction of slope stability using a hybrid stacking ensemble method based on finite element analysis and field data
Slope failures lead to catastrophic consequences in numerous countries and thus the
stability assessment for slopes is of high interest in geotechnical and geological engineering …
stability assessment for slopes is of high interest in geotechnical and geological engineering …
Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam
Flood risk assessment is an important task for disaster management activities in flood-prone
areas. Therefore, it is crucial to develop accurate flood risk assessment maps. In this study …
areas. Therefore, it is crucial to develop accurate flood risk assessment maps. In this study …