Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance
Landslides are one of the catastrophic natural hazards that occur in mountainous areas,
leading to loss of life, damage to properties, and economic disruption. Landslide …
leading to loss of life, damage to properties, and economic disruption. Landslide …
Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility mapping in Icheon, South Korea
Landslides are a geological hazard that can pose a serious threat to human health and the
environment of highlands or mountain slopes. Landslide susceptibility mapping is an …
environment of highlands or mountain slopes. Landslide susceptibility mapping is an …
[HTML][HTML] Assessing the predictive capability of ensemble tree methods for landslide susceptibility mapping using XGBoost, gradient boosting machine, and random …
EK Sahin - SN Applied Sciences, 2020 - Springer
Decision tree-based classifier ensemble methods are a machine learning (ML) technique
that combines several tree models to produce an effective or optimum predictive model, and …
that combines several tree models to produce an effective or optimum predictive model, and …
GIS-based evaluation of landslide susceptibility using hybrid computational intelligence models
W Chen, Y Li - Catena, 2020 - Elsevier
Landslides have caused huge economic and human losses in China. Mapping of landslide
susceptibility is an important tool to prevent and control landslide disasters. The purpose of …
susceptibility is an important tool to prevent and control landslide disasters. The purpose of …
Landslide susceptibility mapping using multiscale sampling strategy and convolutional neural network: A case study in Jiuzhaigou region
Landslides are one of the most widespread natural disasters and pose severe threats to
people, properties, and the environment in many areas. Landslide susceptibility mapping …
people, properties, and the environment in many areas. Landslide susceptibility mapping …
[HTML][HTML] Shallow landslide susceptibility mapping: A comparison between logistic model tree, logistic regression, naïve bayes tree, artificial neural network, and …
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices,
and can cause social upheaval and loss of life. As a result, many scientists study the …
and can cause social upheaval and loss of life. As a result, many scientists study the …
Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning
Predictive capability of landslide susceptibilities is assumed to be varied with different
sampling techniques, such as (a) the landslide scarp centroid,(b) centroid of landslide …
sampling techniques, such as (a) the landslide scarp centroid,(b) centroid of landslide …
[HTML][HTML] GIS based hybrid computational approaches for flash flood susceptibility assessment
Flash floods are one of the most devastating natural hazards; they occur within a catchment
(region) where the response time of the drainage basin is short. Identification of probable …
(region) where the response time of the drainage basin is short. Identification of probable …
Modeling landslide susceptibility using LogitBoost alternating decision trees and forest by penalizing attributes with the bagging ensemble
The major target of this study is to design two novel hybrid integration artificial intelligent
models, which are denoted as LADT-Bagging and FPA-Bagging, for modeling landslide …
models, which are denoted as LADT-Bagging and FPA-Bagging, for modeling landslide …
[HTML][HTML] Landslide susceptibility mapping using machine learning algorithms and remote sensing data in a tropical environment
We used AdaBoost (AB), alternating decision tree (ADTree), and their combination as an
ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands …
ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands …