The past several decades have witnessed an increasing number of natural and manmade
hazards with a dramatic impact on the normal operations of the society. The occurrences of …

This paper aims to provide a five-step conceptual framework to analyze the impacts to the
built environment from multi-hazard interactions. Our methodology includes a critical …

The current study aimed at evaluating the capabilities of seven advanced machine learning
techniques (MLTs), including, Support Vector Machine (SVM), Random Forest (RF) …

Flood has long been known as one of the most catastrophic natural hazards worldwide.
Map** flood-prone areas is an important part of flood disaster management. In this study …

The identification of landslide-prone areas is an essential step in landslide hazard
assessment and mitigation of landslide-related losses. In this study, we applied two novel …

As the spectre of climate change looms large, there is an increasing imperative to develop
comprehensive risk assessment tools. The purpose of this work is to evaluate the evolution …

This study introduces four heterogeneous ensemble-learning techniques, that is, stacking,
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …

Multi-hazard susceptibility prediction is an important component of disasters risk
management plan. An effective multi-hazard risk mitigation strategy includes assessing …

Landslides are abundant in mountainous regions. They are responsible for substantial
damages and losses in those areas. The A1 Highway, which is an important road in Algeria …

Multi-hazard events, characterized by the simultaneous, cascading, or cumulative
occurrence of multiple natural hazards, pose a significant threat to human lives and assets …