[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 …
Artificial intelligence for surface water quality monitoring and assessment: a systematic literature analysis
The goal of this paper was to conduct a systematic literature analysis on the application of
different types of artificial intelligence models in surface water quality monitoring. The …
different types of artificial intelligence models in surface water quality monitoring. The …
Comparisons of heuristic, general statistical and machine learning models for landslide susceptibility prediction and map**
Commonly used data-driven models for landslide susceptibility prediction (LSP) can be
mainly classified as heuristic, general statistical or machine learning models. This study …
mainly classified as heuristic, general statistical or machine learning models. This study …
[HTML][HTML] How do machine learning techniques help in increasing accuracy of landslide susceptibility maps?
Y Achour, HR Pourghasemi - Geoscience Frontiers, 2020 - Elsevier
Landslides are abundant in mountainous regions. They are responsible for substantial
damages and losses in those areas. The A1 Highway, which is an important road in Algeria …
damages and losses in those areas. The A1 Highway, which is an important road in Algeria …
[HTML][HTML] Landslide susceptibility assessment by using convolutional neural network
This study performs a GIS-based landslide susceptibility assessment using a convolutional
neural network, CNN, in a study area of the Gorzineh-khil region, northeastern Iran. For this …
neural network, CNN, in a study area of the Gorzineh-khil region, northeastern Iran. For this …
[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 …
Flood susceptibility assessment in Bangladesh using machine learning and multi-criteria decision analysis
This work proposes a new approach by integrating statistical, machine learning, and multi-
criteria decision analysis, including artificial neural network (ANN), logistic regression (LR) …
criteria decision analysis, including artificial neural network (ANN), logistic regression (LR) …
An integrated approach of machine learning, remote sensing, and GIS data for the landslide susceptibility map**
Landslides triggered in mountainous areas can have catastrophic consequences, threaten
human life, and cause billions of dollars in economic losses. Hence, it is imperative to map …
human life, and cause billions of dollars in economic losses. Hence, it is imperative to map …
Landslide susceptibility evaluation and management using different machine learning methods in the Gallicash River Watershed, Iran
This analysis aims to generate landslide susceptibility maps (LSMs) using various machine
learning methods, namely random forest (RF), alternative decision tree (ADTree) and …
learning methods, namely random forest (RF), alternative decision tree (ADTree) and …
A novel ensemble approach for landslide susceptibility map** (LSM) in Darjeeling and Kalimpong districts, West Bengal, India
Landslides are among the most harmful natural hazards for human beings. This study aims
to delineate landslide hazard zones in the Darjeeling and Kalimpong districts of West …
to delineate landslide hazard zones in the Darjeeling and Kalimpong districts of West …