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 …
[HTML][HTML] Landslide susceptibility zonation method based on C5. 0 decision tree and K-means cluster algorithms to improve the efficiency of risk management
Abstract Machine learning algorithms are an important measure with which to perform
landslide susceptibility assessments, but most studies use GIS-based classification methods …
landslide susceptibility assessments, but most studies use GIS-based classification methods …
Flood detection and susceptibility mapping using sentinel-1 remote sensing data and a machine learning approach: Hybrid intelligence of bagging ensemble based …
Mapping flood-prone areas is a key activity in flood disaster management. In this paper, we
propose a new flood susceptibility mapping technique. We employ new ensemble models …
propose a new flood susceptibility mapping technique. We employ new ensemble models …
Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India
This study is an attempt to quantitatively test and compare novel advanced-machine
learning algorithms in terms of their performance in achieving the goal of predicting flood …
learning algorithms in terms of their performance in achieving the goal of predicting flood …
Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam
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 …
areas. Therefore, it is crucial to develop accurate flood risk assessment maps. In this study …
GIS-based evaluation of landslide susceptibility using hybrid computational intelligence models
W Chen, Y Li - Catena, 2020 - Elsevier
Landslides have caused huge economic and human losses in China. Mapping of landslide
susceptibility is an important tool to prevent and control landslide disasters. The purpose of …
susceptibility is an important tool to prevent and control landslide disasters. The purpose of …
Shallow landslide susceptibility mapping: A comparison between logistic model tree, logistic regression, naïve bayes tree, artificial neural network, and support vector …
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices,
and can cause social upheaval and loss of life. As a result, many scientists study the …
and can cause social upheaval and loss of life. As a result, many scientists study the …
[HTML][HTML] Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer
As threats of landslide hazards have become gradually more severe in recent decades,
studies on landslide prevention and mitigation have attracted widespread attention in …
studies on landslide prevention and mitigation have attracted widespread attention in …
Verification of novel integrations of swarm intelligence algorithms into deep learning neural network for flood susceptibility mapping
This study proposed and compared several novel hybrid models that combined swarm
intelligence algorithms and Deep Learning Neural Network for flood susceptibility mapping …
intelligence algorithms and Deep Learning Neural Network for flood susceptibility mapping …
A comprehensive transferability evaluation of U-Net and ResU-Net for landslide detection from Sentinel-2 data (case study areas from Taiwan, China, and Japan)
Earthquakes and heavy rainfalls are the two leading causes of landslides around the world.
Since they often occur across large areas, landslide detection requires rapid and reliable …
Since they often occur across large areas, landslide detection requires rapid and reliable …