Round Trip Time Prediction Using the Symbolic Function Network Approach

In this paper, we develop a novel approach to model the Internet round trip time using a recently proposed symbolic type neural network model called symbolic function network. The developed predictor is shown to have good generalization performance and simple representation compared to the multilaye...

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Published inarXiv.org
Main Authors Eskander, George S, Atiya, Amir, Kil To Chong, Kim, Hyongsuk, Sung Goo Yoo
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 09.08.2008
Subjects
Multilayer perceptrons
Neural networks
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Abstract In this paper, we develop a novel approach to model the Internet round trip time using a recently proposed symbolic type neural network model called symbolic function network. The developed predictor is shown to have good generalization performance and simple representation compared to the multilayer perceptron based predictors.
AbstractList In this paper, we develop a novel approach to model the Internet round trip time using a recently proposed symbolic type neural network model called symbolic function network. The developed predictor is shown to have good generalization performance and simple representation compared to the multilayer perceptron based predictors.
Author Sung Goo Yoo
Kil To Chong
Eskander, George S
Kim, Hyongsuk
Atiya, Amir
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Neural networks
Title Round Trip Time Prediction Using the Symbolic Function Network Approach
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