Abstract
From the viewpoint of macroscopic dynamic characteristics of urban expressway traffic flow, a commonly used macroscopic dynamic deterministic traffic flow model is analyzed, and the 1.5-layer feed-forward network modeling for the urban expressway traffic flow is established. Hangzhou urban expressway is simulated and the result demonstrates that the neural network model is able to reproduce traffic congestion built in realty with considerable accuracy, thus making it suitable for evaluating various control strategies and performing further modeling and simulation tasks.
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© 2006 Springer-Verlag Berlin Heidelberg
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Shen, GJ. (2006). Traffic Flow Modeling of Urban Expressway Using Artificial Neural Networks. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_3
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DOI: https://doi.org/10.1007/11760191_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34482-7
Online ISBN: 978-3-540-34483-4
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