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Predicting Pedestrian Counts using Machine Learning
3 references·0 citing·16 second hopsampled
Predicting Pedestrian Counts using Machine Learning (2023)Predicting Pedestrian Counts using Machin…Estimates of the Ambient Population: Assessing the Utility of Conventional and Novel Data Sources (2021)Estimates of the Ambient Popu…Quantifying the ambient population using hourly population footfall data and an agent-based model of daily mobility (2019)Quantifying the ambient popul…Exploring the impact of ambient population measures on London crime hotspots (2016)Exploring the impact of ambie…Social Change and Crime Rate Trends: A Routine Activity Approach (1979)The Analysis of Spatial Association by Use of Distance Statistics (1992)Social Change and Crime Rate Trends: A Routine Activity Approach (1979) (2010)Interpretable machine learning models for crime prediction (2022)Leveraging principal component analysis to uncover urban pedestrian dynamics (2025)Understanding pedestrian dynamics using machine learning with real-time urban sensors (2025)Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences (1994)MASON: A Multiagent Simulation Environment (2005)The Multi-Agent Transport Simulation MATSim (2016)Gender Gaps in the Use of Urban Space in Seoul: Analyzing Spatial Patterns of Temporary Populations Using Mobile Phone Data (2020)An analysis of twitter as a relevant human mobility proxy (2022)Calibrating Agent-Based Models Using Uncertainty Quantification Methods (2022)Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)Citizens as sensors: the world of volunteered geography (2007)Social Sensing: A New Approach to Understanding Our Socioeconomic Environments (2015)Intersectional approach of everyday geography (2021)
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References

  • 2016Exploring the impact of ambient population measures on London crime hotspots144 cited
  • 2019Quantifying the ambient population using hourly population footfall data and an agent-based model of daily mobility32 cited
  • 2021Estimates of the Ambient Population: Assessing the Utility of Conventional and Novel Data Sources13 cited

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