Referenced Items are not available for this document.
Freeway traffic flow is a nonlinear and time-variant system, the application of radial basis function (RBF) neural network to freeway macroscopic traffic flow dynamic modeling is presented. A learning algorithm of subtractive clustering method is used to obtain the parameters of radial basis function in this paper, so that RBF neural network has an optimized structure. The simulation results show the algorithm is effective for freeway traffic flow modeling.
Published in:
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
(Volume:6
)
Date of Conference: 15-19 June 2004
- Page(s):
- 5208 - 5211 Vol.6
- Print ISBN:
- 0-7803-8273-0
- INSPEC Accession Number:
- 8190078
- Digital Object Identifier :
- 10.1109/WCICA.2004.1343714
- Product Type:
- Conference Publications
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