Artificial neural network (ANN) aimed to simulate the behavior of the nervous system as well
as the human brain. Neural network models are mathematical computing systems inspired …

Despite yielding considerable degrees of accuracy in landslide predictions, the outcomes of
different landslide susceptibility models are prone to spatial disagreement; and therefore …

Recently, one of the most frequent natural hazards around several regions in the world is the
landslide events. The area of Jabal Farasan in the northwest Jeddah of Saudi Arabia suffers …

In this paper, an inventory of the landslide that occurred in Karahacılı at the end of 2019 was
created and the pre-landslide conditions of the region were evaluated with traditional …

Landslide prediction is complex and involves many factors, such as geotechnical,
geological, topographical, and even meteorological. This work presents a methodology by …

A natural disaster is a natural event which can cause damage to both lives and properties.
The detection of natural disasters is a significant and non-trivial problem. Social media (SM) …

Accurately predicting landslide deformation based on monitoring data is key to successful
early warning of landslide disasters. Landslide displacement–time curves offer an intuitive …

The study proposes a framework combining machine learning (ML) models into a logical
hierarchical system which evaluates the stability of the sheet wall before other predictions …

Due to the population growth and regional economic development, the observed sediment
loads and runoff of the Yellow River have significantly decreased during the last 50 years. It …

Environmental monitoring is a critical process in areas potentially affected by natural
disasters. Nowadays, the distributed processing of vast amounts of heterogeneous sensor …