Accurate short-term traffic flow forecasting has become a crucial step in the overall goal of
better road network management. Previous research [H. Kirby, M. Dougherty, S. Watson …

Much of the current activity in the area of intelligent vehicle-highway systems (IVHSs)
focuses on one simple objective: to collect more data. Clearly, improvements in sensor …

Short term forecasts of traffic flow at a site may need to be based on inputs from several
other sites and times. Neural networks can be readily used for this purpose, because they …

The literature on short-term traffic flow forecasting has undergone great development
recently. Many works, describing a wide variety of different approaches, which very often …

This paper proposes a novel neural network (NN) training method that employs the hybrid
exponential smoothing method and the Levenberg-Marquardt (LM) algorithm, which aims to …

This paper presents a recursive traffic flow prediction algorithm using artificial neural
networks. The system prediction model is specified based on the understanding of how …

This paper presents a new short-term traffic flow prediction system based on an advanced
Time Delay Neural Network (TDNN) model, the structure of which is synthesized using a …

An approach is presented for optimizing short-term traffic-prediction performance by using
multiple topologies of dynamic neural networks and various network-related and traffic …

This brief presents an innovative algorithm integrated with particle swarm optimization and
artificial neural networks to develop short-term traffic flow predictors, which are intended to …

Short-term traffic flow predictions are an essential part of intelligent transportation systems.
Previous research underlines the difficulty in systematically assessing the predictability of …