Recursive prediction of traffic conditions with neural network models
HM Zhang - Journal of Transportation Engineering, 2000 - ascelibrary.org
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 …
networks. The system prediction model is specified based on the understanding of how …
A neural network approach for freeway traffic flow prediction
Traffic flow modeling is an essential component of any traffic control or monitoring system.
This paper presents a new short term traffic flow prediction model based on a feedforward …
This paper presents a new short term traffic flow prediction model based on a feedforward …
A neural network based traffic-flow prediction model
Prediction of traffic-flow in Istanbul has been a great concern for planners of the city. Istanbul
as being one of the most crowded cities in the Europe has a rural population of more than 10 …
as being one of the most crowded cities in the Europe has a rural population of more than 10 …
An urban traffic flow model integrating neural networks
C Ledoux - Transportation Research Part C: Emerging …, 1997 - Elsevier
Over the past few years, artificial intelligence techniques have played important roles in the
design of sophisticated traffic management systems. In this paper, we propose a cooperation …
design of sophisticated traffic management systems. In this paper, we propose a cooperation …
Short-term traffic flow prediction: neural network approach
BL Smith, MJ Demetsky - Transportation Research Record, 1994 - trid.trb.org
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 …
focuses on one simple objective: to collect more data. Clearly, improvements in sensor …
Short-term prediction of traffic flow using a binary neural network
This paper introduces a binary neural network-based prediction algorithm incorporating both
spatial and temporal characteristics into the prediction process. The algorithm is used to …
spatial and temporal characteristics into the prediction process. The algorithm is used to …
Use of sequential learning for short-term traffic flow forecasting
H Chen, S Grant-Muller - Transportation Research Part C: Emerging …, 2001 - Elsevier
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 …
better road network management. Previous research [H. Kirby, M. Dougherty, S. Watson …
Traffic flow forecasting neural networks based on exponential smoothing method
This paper discusses a neural network development approach based on an exponential
smoothing method which aims at enhancing previously used neural networks for traffic flow …
smoothing method which aims at enhancing previously used neural networks for traffic flow …
Macroscopic modeling of freeway traffic using an artificial neural network
H Zhang, SG Ritchie, ZP Lo - Transportation Research …, 1997 - journals.sagepub.com
Traffic flow on freeways is a complex process that often is described by a set of highly
nonlinear, dynamic equations in the form of a macroscopic traffic flow model. However …
nonlinear, dynamic equations in the form of a macroscopic traffic flow model. However …
Short-term traffic flow prediction models-a comparison of neural network and nonparametric regression approaches
BL Smith, MJ Demetsky - Proceedings of IEEE international …, 1994 - ieeexplore.ieee.org
Traffic flow prediction models are expected to play an important role in intelligent vehicle
highway systems. This paper demonstrate that the nearest neighbour models have the …
highway systems. This paper demonstrate that the nearest neighbour models have the …