Abstract
In this paper, an intelligent controller is applied to traffic control of ATM networks. First, the dynamics of the network is modeled by a Locally Linear Neurofuzzy Models. Then, an intelligent controller based on brain emotional learning algorithm is applied to the identified model. Simulation results show that the proposed fuzzy traffic controller can outperform the traditional Usage Parameter Control mechanisms.
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Jalili-Kharaajoo, M., Sadri, M., Roudsari, F.H. (2005). Emotional Learning Based Intelligent Traffic Control of ATM Networks. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_60
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DOI: https://doi.org/10.1007/11427469_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25914-5
Online ISBN: 978-3-540-32069-2
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