Rainfall induced landslide studies in Indian Himalayan region: a critical review
Landslides are one of the most devastating and recurring natural disasters and have
affected several mountainous regions across the globe. The Indian Himalayan region is no …
affected several mountainous regions across the globe. The Indian Himalayan region is no …
Multi-hazard disaster studies: Monitoring, detection, recovery, and management, based on emerging technologies and optimal techniques
Every year man-made and natural disasters impact the lives of millions of people. The
frequency of occurrence of such disasters is steadily increasing since the last 50 years, and …
frequency of occurrence of such disasters is steadily increasing since the last 50 years, and …
Influence of data splitting on performance of machine learning models in prediction of shear strength of soil
The main objective of this study is to evaluate and compare the performance of different
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
A comparative assessment of flood susceptibility modeling using multi-criteria decision-making analysis and machine learning methods
Floods around the world are having devastating effects on human life and property. In this
paper, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS …
paper, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS …
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) …
A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran
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 …
infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due …
Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China
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 …
is to investigate a convolutional neural network (CNN) framework for landslide susceptibility …
[HTML][HTML] GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms
Hazards and disasters have always negative impacts on the way of life. Landslide is an
overwhelming natural as well as man-made disaster that causes loss of natural resources …
overwhelming natural as well as man-made disaster that causes loss of natural resources …
A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility
The main purpose of the present study is to use three state-of-the-art data mining
techniques, namely, logistic model tree (LMT), random forest (RF), and classification and …
techniques, namely, logistic model tree (LMT), random forest (RF), and classification and …