This paper trains a household-level disaster risk classifier based on supervised machine
learning algorithms for cold wave-related disasters. The households' features considered for …

Abstract In this work, Machine Learning (ML) techniques are used to develop tools capable
of accurately predicting the impact of severe weather events. We use readily accessible …

Globally, communities and governments face growing challenges from an increase in
natural disasters and worsening weather extremes. Precision in disaster preparation is …

Unmet healthcare needs in the aftermath of disasters can significantly impede recovery
efforts and exacerbate health disparities among the affected communities. This study aims to …

Weather index insurance is an innovative tool in risk transfer for disasters induced by natural
hazards. This paper proposes a methodology that uses machine learning algorithms for the …

Floods are one of the most frequently occurring disasters in Bangladesh that cause small to
large scale damage every year. Most of the studies in the literature provide a flood damage …

Flood risk, encompassing hazard, exposure, and vulnerability is defined concerning
potential losses. Machine learning techniques have gained traction among researchers to …

The increased severity and frequency of Climate-Induced Disasters (CID) including those
attributed to hydrological, meteorological, and climatological effects have been testing the …

Disaster management activities are carried out before, during, and after the occurrence of a
disaster with the aim of preventing human deaths, protecting people and infrastructure …

The frequency of climate-induced disasters (CID) has exhibited a fivefold increase in the last
five decades. In terms of CID global impact, around 1.7 billion people were affected in the …