Applications of artificial intelligence for disaster management
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …
socioeconomic loss. The actual damage and loss observed in the recent decades has …
[HTML][HTML] Landslide susceptibility mapping 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 …
Review on landslide susceptibility mapping using support vector machines
Y Huang, L Zhao - Catena, 2018 - Elsevier
Landslides are natural phenomena that can cause great loss of life and damage to property.
A landslide susceptibility map is a useful tool to help with land management in landslide …
A landslide susceptibility map is a useful tool to help with land management in landslide …
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 …
Performance evaluation of the GIS-based data mining techniques of best-first decision tree, random forest, and naïve Bayes tree for landslide susceptibility modeling
The main aim of the present study is to explore and compare three state-of-the art data
mining techniques, best-first decision tree, random forest, and naïve Bayes tree, for landslide …
mining techniques, best-first decision tree, random forest, and naïve Bayes tree, for landslide …
Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment
This study developed a deep learning based technique for the assessment of landslide
susceptibility through a one-dimensional convolutional network (1D-CNN) and Bayesian …
susceptibility through a one-dimensional convolutional network (1D-CNN) and Bayesian …
Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms
SVR Termeh, A Kornejady, HR Pourghasemi… - Science of the Total …, 2018 - Elsevier
Flood is one of the most destructive natural disasters which cause great financial and life
losses per year. Therefore, producing susceptibility maps for flood management are …
losses per year. Therefore, producing susceptibility maps for flood management are …
Riverside landslide susceptibility overview: leveraging artificial neural networks and machine learning in accordance with the United Nations (UN) sustainable …
Riverside landslides present a significant geohazard globally, posing threats to
infrastructure and human lives. In line with the United Nations' Sustainable Development …
infrastructure and human lives. In line with the United Nations' Sustainable Development …
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 …
Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using …
The main objective of this study is to evaluate and compare the performance of landslide
models using machine learning ensemble technique for landslide susceptibility assessment …
models using machine learning ensemble technique for landslide susceptibility assessment …