Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …

The volume and availability of data in the Intelligent Transportation System (ITS) result in the
need for data-driven approaches. Big Data algorithms are applied to further enhance the …

As a core technology of Intelligent Transportation System, traffic flow prediction has a wide
range of applications. The fundamental challenge in traffic flow prediction is to effectively …

Robust prediction of citywide traffic flows at different time periods plays a crucial role in
intelligent transportation systems. While previous work has made great efforts to model …

With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …

In this modern era, traffic congestion has become a major source of severe negative
economic and environmental impact for urban areas worldwide. One of the most efficient …

Traffic prediction of wireless networks attracted many researchers and practitioners during
the past decades. However, wireless traffic frequently exhibits strong nonlinearities and …

Deep learning has exploded in the public consciousness, primarily as predictive and
analytical products suffuse our world, in the form of numerous human-centered smart-world …

Short-term passenger demand forecasting is of great importance to the on-demand ride
service platform, which can incentivize vacant cars moving from over-supply regions to over …

Long short-term memory (LSTM) is widely used to process and predict events with time
series, but it is difficult to solve exceedingly long-term dependencies, possibly because the …