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 …
Social vulnerability assessment for landslide hazards in Malaysia: A systematic review study
Landslides represent one of the world's most dangerous and widespread risks, annually
causing thousands of deaths and billions of dollars worth of damage. Building on and …
causing thousands of deaths and billions of dollars worth of damage. Building on and …
Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous …
Heavy rainfall in mountainous terrain can trigger numerous landslides in hill slopes. These
landslides can be deadly to the community living downslope with their fast pace, turning …
landslides can be deadly to the community living downslope with their fast pace, turning …
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 …
Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan
Landslides represent a part of the cascade of geological hazards in a wide range of geo-
environments. In this study, we aim to investigate and compare the performance of two state …
environments. In this study, we aim to investigate and compare the performance of two state …
[HTML][HTML] 基于优化负样本采样策略的梯度提升决策树与随机森林的汶川同震滑坡易发性评价
郭衍昊， 窦杰， 向子林， 马豪， 董傲男， 罗万祺 - 地质科技通报, 2024 - dzkjqb.cug.edu.cn
强震诱发的滑坡具有数量多, 分布广, 规模大等特点, 严重威胁人民生命财产安全.
滑坡易发性评价能够快速预测灾害空间分布, 对于减轻震后灾害的危险性具有重要意义 …
滑坡易发性评价能够快速预测灾害空间分布, 对于减轻震后灾害的危险性具有重要意义 …
Assessing the predictive capability of ensemble tree methods for landslide susceptibility mapping using XGBoost, gradient boosting machine, and random forest
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 …
Shallow landslide susceptibility mapping: A comparison between logistic model tree, logistic regression, naïve bayes tree, artificial neural network, and support vector …
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 …
Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques
The quality of digital elevation models (DEMs), as well as their spatial resolution, are
important issues in geomorphic studies. However, their influence on landslide susceptibility …
important issues in geomorphic studies. However, their influence on landslide susceptibility …
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 …