Traffic Classification of Power Communication Network Based on Improved Hidden Naive Bayes Algorithm

DOI

10.2991/iceeecs-16.2016.188How to use a DOI?

Keywords

Traffic classification; Traffic identification; Hidden Naive Bayes Algorithm

Abstract

With the deepening of power grid construction, power information and communication network bears more and more business. The introduction of network traffic classification is conducive to the rational distribution of network resources, improve service quality. This paper firstly introduces the requirements of traffic classification in electric power communication network, uses flow model based communication network traffic collection technology and machine learning based recognition method, and finally uses the supervised learning algorithm based on machine learning to determine the use of hidden naive Bayes algorithm And classifies the traffic of the power communication network.

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/).

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TY  - CONF
AU  - Lei Lv
AU  - Qing Zhang
AU  - Shilun Zeng
AU  - Hong Wu
PY  - 2016/12
DA  - 2016/12
TI  - Traffic Classification of Power Communication Network Based on Improved Hidden Naive Bayes Algorithm
BT  - Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
PB  - Atlantis Press
SP  - 981
EP  - 985
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.188
DO  - 10.2991/iceeecs-16.2016.188
ID  - Lv2016/12
ER  -