In recent years, the Intelligent transportations system (ITS) has received considerable
attention, due to higher demands for road safety and efficiency in highly interconnected road …

One contemporary policy to deal with traffic congestion is the design and implementation of
forecasting methods that allow users to plan ahead of time and decision makers to improve …

The probabilistic forecasting method described in this study is devised to leverage spatial
and temporal dependency of urban traffic networks, in order to provide predictions accurate …

Accurate traffic information is essential to reduce the adverse effects of road transport in
cities. Today, urban planners and policy-makers demand Intelligent Transportation Systems …

With the increasing availability of traffic data in large urban areas, there is an opportunity to
infer more sophisticated traffic patterns and trends which till now has been difficult to obtain …

Short-term prediction of traffic flows is an important topic for any traffic management control
room. The large availability of real-time data raises not only the expectations for high …

Short-term traffic flow has complicated non-linear characteristic, and it has a similar
seasonality. This paper presents an improved Back Propagation neural network for Short …

The probabilistic forecasting method described in this study is designed to leverage spatial
and temporal dependency of urban traffic networks in order to provide accurate predictions …

Accelerating development of cities and global urbanization process lead to increasing the
transport domain importance that is especially actual within the framework of making the …

Accurate and timely short-term traffic flow predictions can provide useful traffic volume
information beforehand and help people make better route decisions, which plays a vital …