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 …
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 …
A novel ensemble bivariate statistical evidential belief function with knowledge-based analytical hierarchy process and multivariate statistical logistic regression for …
This study compares the landslide susceptibility maps from four application models,
namely,(1) the bivariate model of the Dempster–Shafer based evidential belief function …
namely,(1) the bivariate model of the Dempster–Shafer based evidential belief function …
Landslide susceptibility mapping using an ensemble statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) model at Alborz Mountains (Iran)
The main aim of this paper is to develop a new hybrid method to assess landslide
susceptibility mapping (LSM) in neighboring provinces of Alborz Mountains in Iran. In the …
susceptibility mapping (LSM) in neighboring provinces of Alborz Mountains in Iran. In the …
Landslide susceptibility zonation using the analytical hierarchy process (AHP) in the Bafoussam-Dschang region (West Cameroon)
FL Zangmene, MN Ngapna, MCB Ateba… - Advances in Space …, 2023 - Elsevier
The main goal of this study is to produce a landslide susceptibility map of the Bafoussam-
Dschang region (BDR) which is often subjected to landsliding by using Analytical …
Dschang region (BDR) which is often subjected to landsliding by using Analytical …
Application of Bayesian hyperparameter optimized random forest and XGBoost model for landslide susceptibility mapping
S Wang, J Zhuang, J Zheng, H Fan, J Kong… - Frontiers in Earth …, 2021 - frontiersin.org
Landslides are widely distributed worldwide and often result in tremendous casualties and
economic losses, especially in the Loess Plateau of China. Taking Wuqi County in the …
economic losses, especially in the Loess Plateau of China. Taking Wuqi County in the …
A comparison of information value and logistic regression models in landslide susceptibility mapping by using GIS
This study investigates the application of information value (InV) and logistic regression (LR)
models for producing landslide susceptibility maps (LSMs) of the Zigui–Badong area near …
models for producing landslide susceptibility maps (LSMs) of the Zigui–Badong area near …
Debris flows modeling using geo-environmental factors: developing hybridized deep-learning algorithms
Although the prediction of debris flow-prone areas represents a key step towards reducing
damages, modeling debris flow susceptibility is complicated. In addition, the role of debris …
damages, modeling debris flow susceptibility is complicated. In addition, the role of debris …
Debris-flow susceptibility assessment in China: a comparison between traditional statistical and machine learning methods
H Huang, Y Wang, Y Li, Y Zhou, Z Zeng - Remote Sensing, 2022 - mdpi.com
Debris flows, triggered by dual interferences extrinsically and intrinsically, have been
widespread in China. The debris-flow susceptibility (DFS) assessment is acknowledged as …
widespread in China. The debris-flow susceptibility (DFS) assessment is acknowledged as …
Spatial modeling of snow avalanche using machine learning models and geo-environmental factors: Comparison of effectiveness in two mountain regions
Although snow avalanches are among the most destructive natural disasters, and result in
losses of life and economic damages in mountainous regions, far too little attention has …
losses of life and economic damages in mountainous regions, far too little attention has …