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Predicting Human Mobility during Natural Disasters: A Deep Learning Approach
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Predicting Human Mobility during Natural Disasters: A Deep Learning Approach (2020)Predicting Human Mobility during Natural …Urban mobility and neighborhood isolation in America’s 50 largest cities (2018)Urban mobility and neighborho…Understanding congested travel in urban areas (2016)Understanding congested trave…The TimeGeo modeling framework for urban mobility without travel surveys (2016)The TimeGeo modeling framewor…Patterns and Limitations of Urban Human Mobility Resilience under the Influence of Multiple Types of Natural Disaster (2016)Patterns and Limitations of U…Quantifying Human Mobility Perturbation and Resilience in Hurricane Sandy (2014)Quantifying Human Mobility Pe…Prediction of human emergency behavior and their mobility following large-scale disaster (2014)Prediction of human emergency…Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data (2014)Intra-Urban Human Mobility an…Approaching the Limit of Predictability in Human Mobility (2013)Approaching the Limit of Pred…Spatiotemporal Patterns of Urban Human Mobility (2012)Spatiotemporal Patterns of Ur…Predictability of population displacement after the 2010 Haiti earthquake (2012)Predictability of population …Next place prediction using mobility Markov chains (2012)Next place prediction using m…New Approaches to Human Mobility: Using Mobile Phones for Demographic Research (2012)New Approaches to Human Mobil…Natural disasters and population mobility in Bangladesh (2012)Natural disasters and populat…Collective Response of Human Populations to Large-Scale Emergencies (2011)Collective Response of Human …Limits of Predictability in Human Mobility (2010)Limits of Predictability in H…Understanding individual human mobility patterns (2008)Understanding individual huma…Understanding mobility based on GPS data (2008)Predicting future locations with hidden Markov models (2012)Understanding Human Mobility from Twitter (2015)Power-Law Distributions in Empirical Data (2009)A survey of results on mobile phone datasets analysis (2015)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Power-law distributions in empirical data (2018)Social physics (2022)Theories of International Migration: A Review and Appraisal (1993)At Risk: Natural Hazards, People's Vulnerability and Disasters (1994)Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (2008)Heat stress increases long-term human migration in rural Pakistan (2014)Human Migration in the Era of Climate Change (2019)The impact of climate change on migration: a synthesis of recent empirical insights (2019)The origin of bursts and heavy tails in human dynamics (2005)The scaling laws of human travel (2006)Friendship and mobility (2011)A universal model for mobility and migration patterns (2012)Reality mining: sensing complex social systems (2005)Modelling the scaling properties of human mobility (2010)Computational Social Science (2009)Urban Sensing Using Mobile Phone Network Data: A Survey of Research (2014)Social media for intelligent public information and warning in disasters: An interdisciplinary review (2019)Applications of artificial intelligence for disaster management (2020)Potential Games (1996)The statistical physics of cities (2019)Deconstructing laws of accessibility and facility distribution in cities (2020)Gender gaps in urban mobility (2020)Citizens as sensors: the world of volunteered geography (2007)Human mobility and socioeconomic status: Analysis of Singapore and Boston (2018)A survey on deep learning for human mobility (2023)The Truly Disadvantaged. The Inner City, the Underclass, and Public Policy. By William Julius Wilson. Chicago: University of Chicago Press, 1987. 254p. $19.95. (1988)Assessing “Neighborhood Effects”: Social Processes and New Directions in Research (2002)Neighbourhood effects and beyond: Explaining the paradoxes of inequality in the changing American metropolis (2018)The Neighborhood Effect Averaging Problem (NEAP): An Elusive Confounder of the Neighborhood Effect (2018)Social capital II: determinants of economic connectedness (2022)Combining smart card data and household travel survey to analyze jobs–housing relationships in Beijing (2015)Understanding the tourist mobility using GPS: Where is the next place? (2016)Unveiling hidden migration and mobility patterns in climate stressed regions: A longitudinal study of six million anonymous mobile phone users in Bangladesh (2016)
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References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 2010Limits of Predictability in Human Mobility3,230 cited
  • 2012Natural disasters and population mobility in Bangladesh686 cited
  • 2012Predictability of population displacement after the 2010 Haiti earthquake633 cited
  • 2012Next place prediction using mobility Markov chains555 cited
  • 2016Understanding congested travel in urban areas406 cited
  • 2018Urban mobility and neighborhood isolation in America’s 50 largest cities404 cited
  • 2013Approaching the Limit of Predictability in Human Mobility381 cited
  • 2011Collective Response of Human Populations to Large-Scale Emergencies324 cited
  • 2016The TimeGeo modeling framework for urban mobility without travel surveys295 cited
  • 2012Spatiotemporal Patterns of Urban Human Mobility282 cited
  • 2014Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data216 cited
  • 2012New Approaches to Human Mobility: Using Mobile Phones for Demographic Research196 cited
  • 2016Patterns and Limitations of Urban Human Mobility Resilience under the Influence of Multiple Types of Natural Disaster195 cited
  • 2014Prediction of human emergency behavior and their mobility following large-scale disaster

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183 cited
  • 2014Quantifying Human Mobility Perturbation and Resilience in Hurricane Sandy162 cited
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