State-of-the-art review of geotechnical-driven artificial intelligence techniques in underground soil-structure interaction
There has been an increasing demand for underground construction due to urbanization
and limited land in metropolitan cities in the recent years. However, the behavior of …
and limited land in metropolitan cities in the recent years. However, the behavior of …
Bagging-based machine learning algorithms for landslide susceptibility modeling
T Zhang, Q Fu, H Wang, F Liu, H Wang, L Han - Natural hazards, 2022 - Springer
Landslide hazards have attracted increasing public attention over the past decades due to a
series of catastrophic consequences of landslide occurrence. Thus, the mitigation and …
series of catastrophic consequences of landslide occurrence. Thus, the mitigation and …
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] Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy
The application of ensemble learning models has been continuously improved in recent
landslide susceptibility research, but most studies have no unified ensemble framework …
landslide susceptibility research, but most studies have no unified ensemble framework …
[HTML][HTML] Improved prediction of slope stability using a hybrid stacking ensemble method based on finite element analysis and field data
Slope failures lead to catastrophic consequences in numerous countries and thus the
stability assessment for slopes is of high interest in geotechnical and geological engineering …
stability assessment for slopes is of high interest in geotechnical and geological engineering …
Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)
Landslides are a manifestation of slope instability causing different kinds of damage
affecting life and property. Therefore, high-performance-based landslide prediction models …
affecting life and property. Therefore, high-performance-based landslide prediction models …
Modeling flood susceptibility using data-driven approaches of naïve bayes tree, alternating decision tree, and random forest methods
Floods are one of the most devastating types of disasters that cause loss of lives and
property worldwide each year. This study aimed to evaluate and compare the prediction …
property worldwide each year. This study aimed to evaluate and compare the prediction …
Machine learning ensemble modelling as a tool to improve landslide susceptibility mapping reliability
Statistical landslide susceptibility mapping is a topic in complete and constant evolution,
especially since the introduction of machine learning (ML) methods. A new methodological …
especially since the introduction of machine learning (ML) methods. A new methodological …
GIS based hybrid computational approaches for flash flood susceptibility assessment
Flash floods are one of the most devastating natural hazards; they occur within a catchment
(region) where the response time of the drainage basin is short. Identification of probable …
(region) where the response time of the drainage basin is short. Identification of probable …
Modeling landslide susceptibility using LogitBoost alternating decision trees and forest by penalizing attributes with the bagging ensemble
The major target of this study is to design two novel hybrid integration artificial intelligent
models, which are denoted as LADT-Bagging and FPA-Bagging, for modeling landslide …
models, which are denoted as LADT-Bagging and FPA-Bagging, for modeling landslide …