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STS-EPR: Modelling individual mobility considering the spatial, temporal, and social dimensions together

Articolo
Data di Pubblicazione:
2021
Abstract:
Modelling human mobility is crucial in several scientific areas, from urban planning to epidemic modeling, traffic forecasting, and what-if analysis. On the one hand, existing models focus on the spatial and temporal dimensions of mobility only, while the social dimension is often neglected. On other hand, models that embed a social mechanism have trivial or unrealistic spatial and temporal mechanisms. We propose STS-EPR, a mechanistic model that captures the spatial, temporal, and social dimensions of human mobility together. Our results show that STS-EPR generates realistic trajectories, making it better than models that lack either in the social, the spatial, or the temporal mechanisms. STS-EPR is a step towards the design of mechanistic models that can capture all the aspects of human mobility in a comprehensive way.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Human mobility; Data science; Artificial intelligence; Complex systems
Elenco autori:
Cornacchia, Giuliano; Pappalardo, Luca
Autori di Ateneo:
PAPPALARDO LUCA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/397834
Link al Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/397834/102313/prod_454274-doc_175037.pdf
Pubblicato in:
PROCEDIA COMPUTER SCIENCE
Journal
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URL

https://www.sciencedirect.com/science/article/pii/S1877050921006645
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