Modeling agent decision and behavior in the light of data science and artificial intelligence
Agent-based modeling (ABM) has been widely used in numerous disciplines and practice
domains, subject to many eulogies and criticisms. This article presents key advances and …
domains, subject to many eulogies and criticisms. This article presents key advances and …
A systematic literature review on the use of big data analytics in humanitarian and disaster operations
At the start of this review, 168 million individuals required humanitarian assistance, at the
conclusion of the research, the number had risen to 235 million. Humanitarian aid is critical …
conclusion of the research, the number had risen to 235 million. Humanitarian aid is critical …
Community-scale big data reveals disparate impacts of the Texas winter storm of 2021 and its managed power outage
CC Lee, M Maron, A Mostafavi - Humanities and Social Sciences …, 2022 - nature.com
Aggregated community-scale data could be harnessed to provide insights into the disparate
impacts of managed power outages, burst pipes, and food inaccessibility during extreme …
impacts of managed power outages, burst pipes, and food inaccessibility during extreme …
Quantifying community resilience based on fluctuations in visits to points-of-interest derived from digital trace data
C Podesta, N Coleman, A Esmalian… - Journal of the …, 2021 - royalsocietypublishing.org
This research establishes a methodological framework for quantifying community resilience
based on fluctuations in a population's activity during a natural disaster. Visits to points-of …
based on fluctuations in a population's activity during a natural disaster. Visits to points-of …
Smart flood resilience: harnessing community-scale big data for predictive flood risk monitoring, rapid impact assessment, and situational awareness
Smart resilience is the beneficial result of the collision course of the fields of data science
and urban resilience to flooding. The objective of this study is to propose and demonstrate a …
and urban resilience to flooding. The objective of this study is to propose and demonstrate a …
Spatio-temporal graph convolutional networks for road network inundation status prediction during urban flooding
The objective of this study is to predict the near-future flooding status of road segments
based on their own and adjacent road segments' current status through the use of deep …
based on their own and adjacent road segments' current status through the use of deep …
Characterizing equitable access to grocery stores during disasters using location-based data
Natural hazards cause disruptions in access to critical facilities, such as grocery stores,
impeding residents' ability to prepare for and cope with hardships during the disaster and …
impeding residents' ability to prepare for and cope with hardships during the disaster and …
Adapting social impact assessment to flood risk management
In the context of climate change, a significant increase in the flood risk is expected, which
may lead to an intensification of the social impacts of disasters. Social impacts significantly …
may lead to an intensification of the social impacts of disasters. Social impacts significantly …
Resilience assessment of electrified road networks subject to charging station failures
The number of electric vehicles (EVs) and charging facilities is expected to increase
significantly in the near future, further coupling the existing transportation system with the …
significantly in the near future, further coupling the existing transportation system with the …
Unraveling the temporal importance of community-scale human activity features for rapid assessment of flood impacts
The objective of this research is to explore the temporal importance of community-scale
human activity features for rapid assessment of flood impacts. Ultimate flood impact data …
human activity features for rapid assessment of flood impacts. Ultimate flood impact data …