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 …

Transdermal drug delivery (TDD) is limited by the outer layer of the skin, ie, the stratum
corneum. Research on TDD has become very active in the recent years and various …

Traffic forecasting has emerged as a core component of intelligent transportation systems.
However, timely accurate traffic forecasting, especially long-term forecasting, still remains an …

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 …

The development of Internet of Vehicles (IoV) has produced a considerable amount of real-
time traffic data. These traffic data constitute a kind of digital twin that connects the physical …

The traffic flow prediction is becoming increasingly crucial in Intelligent Transportation
Systems. Accurate prediction result is the precondition of traffic guidance, management, and …

Deep learning approaches have reached a celebrity status in artificial intelligence field, its
success have mostly relied on Convolutional Networks (CNN) and Recurrent Networks. By …

The k-nearest neighbor (KNN) model is an effective statistical model applied in short-term
traffic forecasting that can provide reliable data to guide travelers. This study proposes an …

The ability to timely and accurately forecast the evolution of traffic is very important in traffic
management and control applications. This paper proposes a non-parametric and data …

Traffic prediction, as an important part of intelligent transportation systems, plays a critical
role in traffic state monitoring. While many studies accomplished traffic forecasting task with …