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 …

Machine learning algorithms are increasingly used in various remote sensing applications
due to their ability to identify nonlinear correlations. Ensemble algorithms have been …

This study presents the development of new empirical prediction models to evaluate swell
pressure and unconfined compression strength of expansive soils (P s UCS-ES) using three …

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 …

Floods are one of the most damaging natural hazards causing huge loss of property,
infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due …

Assessments of landslide disasters are becoming increasingly urgent. The aim of this study
is to investigate a convolutional neural network (CNN) framework for landslide susceptibility …

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 …

The main aim of the present study is to explore and compare three state-of-the art data
mining techniques, best-first decision tree, random forest, and naïve Bayes tree, for landslide …

A new artificial intelligence (AI) model, called Bagging-LMT-a combination of bagging
ensemble and Logistic Model Tree (LMT)-is introduced for mapping flood susceptibility. A …

Flood risk assessment is an important task for disaster management activities in flood-prone
areas. Therefore, it is crucial to develop accurate flood risk assessment maps. In this study …