Ad Hoc network traffic prediction based on the Elman neural network
- 10.2991/icmmita-15.2015.312How to use a DOI?
- Traffic prediction; improved Elman neural network; Ad Hoc network
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.
- © 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 - 10.2991/icmmita-15.2015.312 ID - Ding2015/11 ER -