With the aggravation of traffic congestion, traffic flow data (TFD) prediction is very important
for traffic managers to control traffic congestion and for traffic participants to plan their trips …

This paper presents an investigation into the performance of support vector machine (SVM)
in short-term travel-time prediction in comparison with baseline methods, including the …

Intelligent Transportation Systems (ITSs) are systems that aim to provide innovative services
for road users in order to improve traffic efficiency, mobility and safety. This aspect of safety …

Short‐term traffic flow prediction is an important component of intelligent transportation
systems, which can support traffic trip planning and traffic management. Although existing …

In this study, we present the EEG-GCN, a novel hybrid model for the prediction of time series
data, adept at addressing the inherent challenges posed by the data's complex, non-linear …

To analyze the changing characteristics of ship traffic flow in wind farms water area, and to
improve the accuracy of ship traffic flow prediction, a Gated Recurrent Unit (GRU) of a …

Traffic flow prediction plays an important role in intelligent transportation system (ITS).
However, due to the randomness and complex periodicity of traffic flow data, traditional …

The aim of this research is to predict the total and average monthly night traffic on state
roads in Serbia, using the technique of supervised machine learning. A set of data on total …

Real-time traffic data at intersections is significant for development of adaptive traffic light
control systems. Sensors such as infrared radiation and GPS are not capable of providing …

Accurate and real-time traffic flow prediction is crucial in intelligent transportation systems
(ITS), and the traditional shallow prediction methods are challenging to capture the …