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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 …
[HTML][HTML] Landslide susceptibility maps of Italy: Lesson learnt from dealing with multiple landslide types and the uneven spatial distribution of the national inventory
Landslide susceptibility corresponds to the probability of landslide occurrence across a
given geographic space. This probability is usually estimated by using a binary classifier …
given geographic space. This probability is usually estimated by using a binary classifier …
Assessment of landslide susceptibility map** based on Bayesian hyperparameter optimization: A comparison between logistic regression and random forest
This study aims to develop two optimized models of landslide susceptibility map** (LSM),
ie, logical regression (LR) and random forest (RF) models, premised on hyperparameter …
ie, logical regression (LR) and random forest (RF) models, premised on hyperparameter …
Application of alternating decision tree with AdaBoost and bagging ensembles for landslide susceptibility map**
Landslides are a common type of natural disaster that brings great threats to the human lives
and economic development around the world, especially in the Chinese Loess Plateau …
and economic development around the world, especially in the Chinese Loess Plateau …
AI-powered landslide susceptibility assessment in Hong Kong
Landslide susceptibility assessment is essential for regional landslide risk assessment and
mitigation. Most past studies involved cell-based analysis that takes landslide incidents as …
mitigation. Most past studies involved cell-based analysis that takes landslide incidents as …
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 …
Enhancing flood susceptibility modeling using multi-temporal SAR images, CHIRPS data, and hybrid machine learning algorithms
Flood susceptibility maps are useful tool for planners and emergency management
professionals in the early warning and mitigation stages of floods. In this study, Sentinel-1 …
professionals in the early warning and mitigation stages of floods. In this study, Sentinel-1 …
Landslide susceptibility assessment for Maragheh County, Iran, using the logistic regression algorithm
Landslide susceptibility assessment is the globally approved procedure to prepare geo-
hazard maps of landslide-prone areas, which are highly used in urban management and …
hazard maps of landslide-prone areas, which are highly used in urban management and …
[HTML][HTML] Explainable artificial intelligence in geoscience: A glimpse into the future of landslide susceptibility modeling
For decades, the distinction between statistical models and machine learning ones has
been clear. The former are optimized to produce interpretable results, whereas the latter …
been clear. The former are optimized to produce interpretable results, whereas the latter …