Application of artificial intelligence in geotechnical engineering: A state-of-the-art review
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
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 …
Deep learning-based landslide susceptibility mapping
Landslides are considered as one of the most devastating natural hazards in Iran, causing
extensive damage and loss of life. Landslide susceptibility maps for landslide prone areas …
extensive damage and loss of life. Landslide susceptibility maps for landslide prone areas …
[HTML][HTML] A review of statistically-based landslide susceptibility models
In this paper, we do a critical review of statistical methods for landslide susceptibility
modelling and associated terrain zonations. Landslide susceptibility is the likelihood of a …
modelling and associated terrain zonations. Landslide susceptibility is the likelihood of a …
[HTML][HTML] Landslide susceptibility zonation method based on C5. 0 decision tree and K-means cluster algorithms to improve the efficiency of risk management
Abstract Machine learning algorithms are an important measure with which to perform
landslide susceptibility assessments, but most studies use GIS-based classification methods …
landslide susceptibility assessments, but most studies use GIS-based classification methods …
[HTML][HTML] Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin, Asir Region, Saudi Arabia
AM Youssef, HR Pourghasemi - Geoscience Frontiers, 2021 - Elsevier
The current study aimed at evaluating the capabilities of seven advanced machine learning
techniques (MLTs), including, Support Vector Machine (SVM), Random Forest (RF) …
techniques (MLTs), including, Support Vector Machine (SVM), Random Forest (RF) …
Application of alternating decision tree with AdaBoost and bagging ensembles for landslide susceptibility mapping
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 …
[HTML][HTML] Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future
Landslides are geomorphological processes that shape the landscapes of all continents,
dismantling mountains and contributing sediments to the river networks. Caused by …
dismantling mountains and contributing sediments to the river networks. Caused by …
Prediction of the landslide susceptibility: Which algorithm, which precision?
HR Pourghasemi, O Rahmati - Catena, 2018 - Elsevier
Coupling machine learning algorithms with spatial analytical techniques for landslide
susceptibility modeling is a worth considering issue. So, the current research intend to …
susceptibility modeling is a worth considering issue. So, the current research intend to …
[HTML][HTML] Landslide susceptibility assessment by using convolutional neural network
This study performs a GIS-based landslide susceptibility assessment using a convolutional
neural network, CNN, in a study area of the Gorzineh-khil region, northeastern Iran. For this …
neural network, CNN, in a study area of the Gorzineh-khil region, northeastern Iran. For this …