Data sources and approaches for building occupancy profiles at the urban scale–A review
Buildings' occupant profiles at the urban scale play an important role in various applications
like Urban Building Energy Modeling (UBEM) and assessing energy consumption patterns …
like Urban Building Energy Modeling (UBEM) and assessing energy consumption patterns …
Establishing the integrated science of movement: bringing together concepts and methods from animal and human movement analysis
Movement analysis has become an integral part of many disciplines, yet with relatively little
overlap. A foresight paper in this journal entitled “Towards an integrated science of …
overlap. A foresight paper in this journal entitled “Towards an integrated science of …
Where would i go next? large language models as human mobility predictors
Accurate human mobility prediction underpins many important applications across a variety
of domains, including epidemic modelling, transport planning, and emergency responses …
of domains, including epidemic modelling, transport planning, and emergency responses …
Spatio-temporal urban knowledge graph enabled mobility prediction
With the rapid development of the mobile communication technology, mobile trajectories of
humans are massively collected by Internet service providers (ISPs) and application service …
humans are massively collected by Internet service providers (ISPs) and application service …
Urban human mobility: Data-driven modeling and prediction
Human mobility is a multidisciplinary field of physics and computer science and has drawn a
lot of attentions in recent years. Some representative models and prediction approaches …
lot of attentions in recent years. Some representative models and prediction approaches …
[HTML][HTML] Context-aware multi-head self-attentional neural network model for next location prediction
Accurate activity location prediction is a crucial component of many mobility applications and
is particularly required to develop personalized, sustainable transportation systems. Despite …
is particularly required to develop personalized, sustainable transportation systems. Despite …
Semantic-aware spatio-temporal app usage representation via graph convolutional network
Recent years have witnessed a rapid proliferation of personalized mobile Apps, which
poses a pressing need for user experience improvement. A promising solution is to model …
poses a pressing need for user experience improvement. A promising solution is to model …
Mobility prediction via rule-enhanced knowledge graph
With the rapid development of location acquisition technologies, massive mobile trajectories
have been collected and made available to us, which support a fantastic way of …
have been collected and made available to us, which support a fantastic way of …
Attentional Markov model for human mobility prediction
Accurate human mobility prediction is important for many applications in wireless networks,
including intelligent content caching and prefetching, network optimization, etc. However …
including intelligent content caching and prefetching, network optimization, etc. However …
Cross-and Context-Aware Attention Based Spatial-Temporal Graph Convolutional Networks for Human Mobility Prediction
The COVID-19 pandemic has dramatically transformed human mobility patterns. Therefore,
human mobility prediction for the “new normal” is crucial to infrastructure redesign …
human mobility prediction for the “new normal” is crucial to infrastructure redesign …