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 …
Applications of artificial intelligence for disaster management
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …
socioeconomic loss. The actual damage and loss observed in the recent decades has …
Regional rainfall-induced landslide hazard warning based on landslide susceptibility mapping and a critical rainfall threshold
Rainfall-induced landslide hazard warning, which refers to the prediction of the spatial-
temporal probability of landslide occurrence in a certain area under the conditions of …
temporal probability of landslide occurrence in a certain area under the conditions of …
[HTML][HTML] Landslide susceptibility mapping using machine learning: A literature survey
Landslide is a devastating natural disaster, causing loss of life and property. It is likely to
occur more frequently due to increasing urbanization, deforestation, and climate change …
occur more frequently due to increasing urbanization, deforestation, and climate change …
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 …
A deep learning algorithm using a fully connected sparse autoencoder neural network for landslide susceptibility prediction
The environmental factors of landslide susceptibility are generally uncorrelated or non-
linearly correlated, resulting in the limited prediction performances of conventional machine …
linearly correlated, resulting in the limited prediction performances of conventional machine …
Landslide susceptibility prediction based on a semi-supervised multiple-layer perceptron model
Conventional supervised and unsupervised machine learning models used for landslide
susceptibility prediction (LSP) have many drawbacks, such as an insufficient number of …
susceptibility prediction (LSP) have many drawbacks, such as an insufficient number of …
[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) …
[HTML][HTML] Applications of machine learning methods for engineering risk assessment–A review
The purpose of this article is to present a structured review of publications utilizing machine
learning methods to aid in engineering risk assessment. A keyword search is performed to …
learning methods to aid in engineering risk assessment. A keyword search is performed to …
Review on landslide susceptibility mapping using support vector machines
Y Huang, L Zhao - Catena, 2018 - Elsevier
Landslides are natural phenomena that can cause great loss of life and damage to property.
A landslide susceptibility map is a useful tool to help with land management in landslide …
A landslide susceptibility map is a useful tool to help with land management in landslide …