Network performance evaluation algorithm based on BP neural network
Authors
Qi Liu, Xiyue Wang, Yiyong Lin, Ling He, Yunzhi Huang
Corresponding Author
Qi Liu
Available Online June 2016.
- DOI
- 10.2991/mmebc-16.2016.466How to use a DOI?
- Keywords
- Net performance evaluation BP neural network Cross validation
- Abstract
In this paper, a network performance evaluation algorithm is proposed based on BP neural network. This system collects 8 network parameters in a local area network, and classifies the performance of network into three states: excellent, good and unqualified. Verification and analysis results show that the accuracy of the proposed network performance evaluation algorithm reaches up to 90% by K-fold cross validation test. The experiments indicate that this proposed algorithm is robust and effective. Moreover, the calculation time of this system is less than 1ms. It could be effectively applied for a real-time network performance evaluation.
- Copyright
- © 2016, 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 - Qi Liu AU - Xiyue Wang AU - Yiyong Lin AU - Ling He AU - Yunzhi Huang PY - 2016/06 DA - 2016/06 TI - Network performance evaluation algorithm based on BP neural network BT - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer PB - Atlantis Press SP - 2314 EP - 2317 SN - 2352-5401 UR - https://doi.org/10.2991/mmebc-16.2016.466 DO - 10.2991/mmebc-16.2016.466 ID - Liu2016/06 ER -