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Information Technology Journal
  Year: 2014 | Volume: 13 | Issue: 3 | Page No.: 593-596
DOI: 10.3923/itj.2014.593.596
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Research of Delay Prediction Based on RBF Neural Network

Guodong Li, Pengfei Jin and Kai Li

The existence of time-varying network delay will have some negative impacts on some network services. The dynamic changes of network delay reflect the load characteristics of network path. An important basis for the implementation of congestion control and routing is the accurate prediction of network delay. In this paper, a delay prediction model based on Radial Basis Function (RBF) neural network is establishe which is trained by APC-III algorithm and the method of least squares. This model avoids the cumbersome process of model structure identification and model checking in traditional time-series analysis and overcomes the shortcoming that the traditional neural network can easily fall into local extremum and overtraining. The simulation results show that this model can predict network delay with high accuracy.
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How to cite this article:

Guodong Li, Pengfei Jin and Kai Li, 2014. Research of Delay Prediction Based on RBF Neural Network. Information Technology Journal, 13: 593-596.

DOI: 10.3923/itj.2014.593.596






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