Jun 15, 2017 · We present a solution to model user transitions and mobility patterns without the need of accessing any cloud services, and thus completely ...
This work focuses on analysis and model generation for user mobility patterns given a sequence of observed WiFi signals. Built on the Android platform, ...
May 2, 2024 · Parametric models flexible enough to capture all mobility patterns that an expert believes are possible are often large, requiring a great deal ...
In this paper, a probabilistic topic modeling algorithm called Latent Dirichlet Allocation (LDA) is implemented to infer trip purposes from activity attributes.
Missing: Transition | Show results with:Transition
In this survey, we review human mobility models based on a human-centric angle in a data- driven context. Specifically, we characterize human mobil- ity ...
Aug 16, 2018 · Abstract: Modeling human mobility is a critical task in fields such as urban planning, ecology, and epidemiology.
May 8, 2024 · In this paper, we investigate spontaneous mobility changes without stay-at-home orders throughout a highly infectious pandemic.
May 24, 2024 · We develop a novel generative deep learning approach for human mobility modeling and synthesis, using ubiquitous and open-source data.
Sep 16, 2021 · Human mobility data are indispensable in modeling large-scale epidemics, especially in predicting the spatial spread of diseases and in ...
In this paper we propose the d-EPR model, which exploits collective information and the gravity model to drive the movements of an individual.