Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications

Ad Hoc network traffic prediction based on the Elman neural network

Authors
Yuanming Ding, Jiayao Gao, Xue Wang
Corresponding Author
Yuanming Ding
Available Online November 2015.
DOI
https://doi.org/10.2991/icmmita-15.2015.312How to use a DOI?
Keywords
Traffic prediction; improved Elman neural network; Ad Hoc network
Abstract

For complex Ad Hoc network environment, based on Elman neural network prediction model, using particle swarm optimization algorithm to optimize the original Elman BP training can find the global optimization thresholds and weights of the neural network layers, and a modified Elman neural network model is proposed to predict the Ad Hoc network node traffic. According to Ad Hoc network node traffic data obtained by simulation in NS-2, network traffic predict experiment results show that the modified Elman neural network model has improved compared to the previous Elman neural network model and has a lower error and higher prediction accuracy.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications
Series
Advances in Computer Science Research
Publication Date
November 2015
ISBN
978-94-6252-120-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmmita-15.2015.312How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yuanming Ding
AU  - Jiayao Gao
AU  - Xue Wang
PY  - 2015/11
DA  - 2015/11
TI  - Ad Hoc network traffic prediction based on the Elman neural network
BT  - Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 1678
EP  - 1683
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-15.2015.312
DO  - https://doi.org/10.2991/icmmita-15.2015.312
ID  - Ding2015/11
ER  -