[HTML][HTML] Landslide susceptibility map** using machine learning: A literature survey
Landslide is a devastating natural disaster, causing loss of life and property. It is likely to
occur more frequently due to increasing urbanization, deforestation, and climate change …
occur more frequently due to increasing urbanization, deforestation, and climate change …
Flash-flood hazard using deep learning based on H2O R package and fuzzy-multicriteria decision-making analysis
The present study was done in order to simulate the flash-flood susceptibility across the
Suha river basin in Romania using a number of 3 hybrid models and fuzzy-AHP multicriteria …
Suha river basin in Romania using a number of 3 hybrid models and fuzzy-AHP multicriteria …
Novel evolutionary-optimized neural network for predicting landslide susceptibility
In order to mitigate/prevent the risks of landslides, one of the essential tools that can be used
to manage and plan the development of human settlements is landslide susceptibility. The …
to manage and plan the development of human settlements is landslide susceptibility. The …
Landslide susceptibility assessment of a part of the Western Ghats (India) employing the AHP and F-AHP models and comparison with existing susceptibility maps
Landslides are prevalent in the Western Ghats, and the incidences that happened in 2021 in
the Koottickal area of the Kottayam district (Western Ghats) resulted in the loss of 10 lives …
the Koottickal area of the Kottayam district (Western Ghats) resulted in the loss of 10 lives …
An ensemble random forest tree with SVM, ANN, NBT, and LMT for landslide susceptibility map** in the Rangit River watershed, India
This study examined landslide susceptibility, an increasingly common problem in
mountainous regions across the world as a result of urbanization, deforestation, and various …
mountainous regions across the world as a result of urbanization, deforestation, and various …
Flash-flood potential map** using deep learning, alternating decision trees and data provided by remote sensing sensors
There is an evident increase in the importance that remote sensing sensors play in the
monitoring and evaluation of natural hazards susceptibility and risk. The present study aims …
monitoring and evaluation of natural hazards susceptibility and risk. The present study aims …
Improving GALDIT-based groundwater vulnerability predictive map** using coupled resampling algorithms and machine learning models
Develo** accurate groundwater vulnerability maps is important for the sustainable
management of groundwater resources. In this research, resampling methods [eg, Bootstrap …
management of groundwater resources. In this research, resampling methods [eg, Bootstrap …
[HTML][HTML] Spatial prediction of landslide susceptibility using logistic regression (LR), functional trees (FTs), and random subspace functional trees (RSFTs) for Pengyang …
Landslides pose significant and serious geological threat disasters worldwide, threatening
human lives and property; China is particularly susceptible to these disasters. This paper …
human lives and property; China is particularly susceptible to these disasters. This paper …
GIS-based ensemble computational models for flood susceptibility prediction in the Quang Binh Province, Vietnam
Recently, floods are occurring more frequently every year around the world due to increased
anthropogenic activities and climate change. There is a need to develop accurate models for …
anthropogenic activities and climate change. There is a need to develop accurate models for …
Predicting landslide susceptibility based on decision tree machine learning models under climate and land use changes
QB Pham, S Chandra Pal, R Chakrabortty… - Geocarto …, 2022 - Taylor & Francis
Landslides are most catastrophic and frequently occurred across the world. In mountainous
areas of the globe, recurrent occurrences of landslide have caused huge amount of …
areas of the globe, recurrent occurrences of landslide have caused huge amount of …