Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

Recent years include the world's hottest year, while they have been marked mainly, besides
the COVID-19 pandemic, by climate-related disasters, based on data collected by the …

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

This paper performed a systematic review of the various machine learning (ML) techniques
applied to assess the health condition of heritage buildings. More robust predictive models …

In the current report, characteristics of the propagated wave in a sandwich structure with a
soft core and multi-hybrid nanocomposite (MHC) face sheets are investigated. The higher …

In this research, a mathematical derivation is made to develop a nonlinear dynamic model
for the nonlinear frequency and chaotic responses of the multi-scale hybrid nano-composite …

Stability of the soil slopes is one of the most challenging issues in civil engineering projects.
Due to the complexity and non-linearity of this threat, utilizing simple predictive models does …

In this article, smart control and frequency characteristics of a graphene nanoplatelets
composite (GPLRC) cylindrical shell surrounded by piezoelectric layers as sensor and …

In this article, amplitude, and vibrational characteristics of a rotating fiber metal laminated
microdisk are presented. The current microstructure is modeled as a flexible microdisk …

The robustness of landslide prediction models has become a major focus of researchers
worldwide. We developed two novel hybrid predictive models that combine the self …