Forecasting the time of failure of landslides at slope-scale is a difficult yet important task that
can mitigate the effects of slope failures in terms of both human lives and economic losses …

Landslides are one of the most critical categories of natural disasters worldwide and induce
severely destructive outcomes to human life and the overall economic system. To reduce its …

Accurate early warning systems for landslides are a reliable risk-reduction strategy that may
significantly reduce fatalities and economic losses. Several machine learning methods have …

Abstract Machine learning (ML) has been extensively applied to model geohazards, yielding
tremendous success. However, researchers and practitioners still face challenges in …

Recently, integrated machine learning (ML) metaheuristic algorithms, such as the artificial
bee colony (ABC) algorithm, genetic algorithm (GA), gray wolf optimization (GWO) algorithm …

A good prediction of landslide displacement is an essential component for implementing an
early warning system. In the Three Gorges Reservoir Area (TGRA), many landslides deform …

The application of artificial intelligence (AI) and machine learning in geohazard modelling
has been rapidly growing in recent years, a trend that is observed in several research and …

The landslide displacement in the Three Gorges Reservoir, China, experiences step-like
deformation that is influenced by rainfall and the periodic scheduling of the reservoir. In view …

Landslide prediction is important for mitigating geohazards but is very challenging. In
landslide evolution, displacement depends on the local geological conditions and variations …

This paper proposes a multivariate chaotic Extreme Learning Machine (ELM) model for the
prediction of the displacement of reservoir landslides. The displacement time series of the …