Examining the Limits of Predictability of Human Mobility

We challenge the upper bound of human-mobility predictability that is widely used to corroborate the accuracy of mobility prediction models. We observe that extensions of recurrent-neural network architectures achieve significantly higher prediction accuracy, surpassing this upper bound. Given this...

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Detalles Bibliográficos
Autores principales: Kulkarni, Vaibhav, Mahalunkar, Abhijit, Garbinato, Benoit, Kelleher, John D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514921/
https://www.ncbi.nlm.nih.gov/pubmed/33267146
http://dx.doi.org/10.3390/e21040432

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514921/
https://www.ncbi.nlm.nih.gov/pubmed/33267146
http://dx.doi.org/10.3390/e21040432

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