Machine learning and landslide studies: recent advances and applications
Upon the introduction of machine learning (ML) and its variants, in the form that we know
today, to the landslide community, many studies have been carried out to explore the …
today, to the landslide community, many studies have been carried out to explore the …
[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 …
Flash flood susceptibility modeling using new approaches of hybrid and ensemble tree-based machine learning algorithms
Flash flooding is considered one of the most dynamic natural disasters for which measures
need to be taken to minimize economic damages, adverse effects, and consequences by …
need to be taken to minimize economic damages, adverse effects, and consequences by …
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 …
Mapping and holistic design of natural hydraulic lime mortars
In recent years, the study of high hydraulicity natural hydraulic lime (NHL5) mortars has
been in the focus of many researchers, as it is considered a compatible, eco-friendly binding …
been in the focus of many researchers, as it is considered a compatible, eco-friendly binding …
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 …
Soft computing ensemble models based on logistic regression for groundwater potential mapping
Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …
groundwater storage resources. In this study, we proposed four ensemble soft computing …
Landslide spatial modelling using novel bivariate statistical based Naïve Bayes, RBF Classifier, and RBF Network machine learning algorithms
Q He, H Shahabi, A Shirzadi, S Li, W Chen… - Science of the total …, 2019 - Elsevier
Landslides are major hazards for human activities often causing great damage to human
lives and infrastructure. Therefore, the main aim of the present study is to evaluate and …
lives and infrastructure. Therefore, the main aim of the present study is to evaluate and …
Evaluation efficiency of hybrid deep learning algorithms with neural network decision tree and boosting methods for predicting groundwater potential
Y Chen, W Chen, S Chandra Pal, A Saha… - Geocarto …, 2022 - Taylor & Francis
Delineation of the groundwater's potential zones is a growing phenomenon worldwide due
to the high demand for fresh groundwater. Therefore, the identification of potential …
to the high demand for fresh groundwater. Therefore, the identification of potential …