As an important part of the intelligent transportation system (ITS), short‐term traffic prediction
has become a hot research topic in the field of traffic engineering. In recent years, with the …

Short‐term traffic flow prediction is fundamental for the intelligent transportation system and
is proved to be a challenge. This paper proposed a hybrid strategy that is general and can …

Some researchers treat traffic flow as an entirety while predicting short-term traffic flow.
Through analyzing real-world traffic flow, we have found that urban traffic shows a stable …

The information of network-wide future traffic speed distribution and its propagation is
beneficial to develop proactive traffic congestion management strategies. However …

A short-term traffic flow prediction framework is proposed for urban road networks based on
data-driven methods that mainly include two modules. The first module contains a set of …

The traffic flow prediction plays a key role in modern Intelligent Transportation Systems (ITS).
Although great achievements have been made in traffic flow prediction, it is still a challenge …

Recent years have seen the emergence of two significant technologies: big data systems
capable of storing, retrieving, and processing large amounts of data, and machine learning …

Short-term traffic forecasting based on deep learning methods, especially recurrent neural
networks (RNN), has received much attention in recent years. However, the potential of RNN …

Accurate and stable short-term traffic flow prediction is an indispensable part in current
intelligent transportation systems. In this paper, a novel short-term traffic flow forecasting …

With the increasing demand for intelligent transportation systems, short-term traffic flow
prediction has become an important research direction. The memory unit of a Long Short …