A Deep Gravity model for mobility flows generation

The movements of individuals within and among cities influence critical aspects of our society, such as well-being, the spreading of epidemics, and the quality of the environment. Here, the authors use deep neural networks to discover non-linear relationships between geographical variables and mobil...

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Autores principales:	Filippo Simini, Gianni Barlacchi, Massimilano Luca, Luca Pappalardo
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/059d39bef08745cab26256153f00f062
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id	oai:doaj.org-article:059d39bef08745cab26256153f00f062
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spelling	oai:doaj.org-article:059d39bef08745cab26256153f00f0622021-11-14T12:34:21ZA Deep Gravity model for mobility flows generation10.1038/s41467-021-26752-42041-1723https://doaj.org/article/059d39bef08745cab26256153f00f0622021-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-26752-4https://doaj.org/toc/2041-1723The movements of individuals within and among cities influence critical aspects of our society, such as well-being, the spreading of epidemics, and the quality of the environment. Here, the authors use deep neural networks to discover non-linear relationships between geographical variables and mobility flows.Filippo SiminiGianni BarlacchiMassimilano LucaLuca PappalardoNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Filippo Simini Gianni Barlacchi Massimilano Luca Luca Pappalardo A Deep Gravity model for mobility flows generation
description	The movements of individuals within and among cities influence critical aspects of our society, such as well-being, the spreading of epidemics, and the quality of the environment. Here, the authors use deep neural networks to discover non-linear relationships between geographical variables and mobility flows.
format	article
author	Filippo Simini Gianni Barlacchi Massimilano Luca Luca Pappalardo
author_facet	Filippo Simini Gianni Barlacchi Massimilano Luca Luca Pappalardo
author_sort	Filippo Simini
title	A Deep Gravity model for mobility flows generation
title_short	A Deep Gravity model for mobility flows generation
title_full	A Deep Gravity model for mobility flows generation
title_fullStr	A Deep Gravity model for mobility flows generation
title_full_unstemmed	A Deep Gravity model for mobility flows generation
title_sort	deep gravity model for mobility flows generation
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/059d39bef08745cab26256153f00f062
work_keys_str_mv	AT filipposimini adeepgravitymodelformobilityflowsgeneration AT giannibarlacchi adeepgravitymodelformobilityflowsgeneration AT massimilanoluca adeepgravitymodelformobilityflowsgeneration AT lucapappalardo adeepgravitymodelformobilityflowsgeneration AT filipposimini deepgravitymodelformobilityflowsgeneration AT giannibarlacchi deepgravitymodelformobilityflowsgeneration AT massimilanoluca deepgravitymodelformobilityflowsgeneration AT lucapappalardo deepgravitymodelformobilityflowsgeneration
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A Deep Gravity model for mobility flows generation

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