Machine learning for landslides prevention: a survey
Landslides are one of the most critical categories of natural disasters worldwide and induce
severely destructive outcomes to human life and the overall economic system. To reduce its …
severely destructive outcomes to human life and the overall economic system. To reduce its …
Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility
In recent decades, data-driven landslide susceptibility models (DdLSM), which are based on
statistical or machine learning approaches, have become popular to estimate the relative …
statistical or machine learning approaches, have become popular to estimate the relative …
Assessment of landslide susceptibility map** based on Bayesian hyperparameter optimization: A comparison between logistic regression and random forest
D Sun, J Xu, H Wen, D Wang - Engineering Geology, 2021 - Elsevier
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 …
Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling
Statistical and now machine learning prediction methods have been gaining popularity in
the field of landslide susceptibility modeling. Particularly, these data driven approaches …
the field of landslide susceptibility modeling. Particularly, these data driven approaches …
Assessment of the effects of training data selection on the landslide susceptibility map**: a comparison between support vector machine (SVM), logistic regression …
Landslide is a natural hazard that results in many economic damages and human losses
every year. Numerous researchers have studied landslide susceptibility map** (LSM) …
every year. Numerous researchers have studied landslide susceptibility map** (LSM) …
Comparison of a logistic regression and Naïve Bayes classifier in landslide susceptibility assessments: The influence of models complexity and training dataset size
The main objective of the present study was to compare the performance of a classifier that
implements the Logistic Regression and a classifier that employs a Naïve Bayes algorithm in …
implements the Logistic Regression and a classifier that employs a Naïve Bayes algorithm in …
Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)
The aim of this work is to define reliable susceptibility models for shallow landslides using
Logistic Regression and Random Forests multivariate statistical techniques. The study area …
Logistic Regression and Random Forests multivariate statistical techniques. The study area …
[HTML][HTML] Presenting logistic regression-based landslide susceptibility results
A new work-flow is proposed to unify the way the community shares Logistic Regression
results for landslide susceptibility purposes. Although Logistic Regression models and …
results for landslide susceptibility purposes. Although Logistic Regression models and …
Map** landslide susceptibility using data-driven methods
Most epistemic uncertainty within data-driven landslide susceptibility assessment results
from errors in landslide inventories, difficulty in identifying and map** landslide causes …
from errors in landslide inventories, difficulty in identifying and map** landslide causes …
[HTML][HTML] National-scale data-driven rainfall induced landslide susceptibility map** for China by accounting for incomplete landslide data
China is one of the countries where landslides caused the most fatalities in the last decades.
The threat that landslide disasters pose to people might even be greater in the future, due to …
The threat that landslide disasters pose to people might even be greater in the future, due to …