Reusable Synthetic Population Data Generation
- Andrew Crooks
- “Richard” Na Jiang
Student and Senior Collaborators
- Hamdi Kavak (Faculty collaborator)
- William Kennedy (Faculty collaborator)
- Annetta Burger (Former student collaborator)
Synthetic populations are of vital interest to Agent-Based Models to create realistic models. This study introduces a new approach that generates a reusable synthetic population using the New York Metro Area as a study area. Our method directly incorporates social networks (i.e., connections within a family or workplace) when creating a synthetic population. To demonstrate the utility and reusability of the synthetic population and to highlight the role of social networks, we show two example applications: traffic dynamics and the spread of disease. These applications demonstrate how other researchers can efficiently utilize our synthetic population method for different modeling problems.
Recently this study is extended to cover more examples and has been accepted to appear in the Journal of Computational Urban Science.
Publications & Presentations
- Generation of Reusable Synthetic Population and Social Networks for Agent-Based Modeling
N. Jiang, H. Kavak, W.G. Kennedy, and A. Crooks 2021 Annual Modeling and Simulation Conference (ANNSIM), Fairfax, VA, USA (Online), July 19-22, 2021
Last updated on Jan 30, 2022.