Bandwidth Prediction for Business Requirement of Electric Power Communication Network with Deep-Learning

DOI

10.2991/iwmecs-18.2018.109How to use a DOI?

Keywords

Electric power communication network, Bandwidth prediction, Deep learning, Principal component analysis, Affect system data.

Abstract

With the power-supply system information management,it puts forward higher requirement about network bandwidth. Power communication network bandwidth predictive based on business requirement not only ensures smooth of communication, but also is the key technology of enhancing broadband usage. The paper relying on the province power company as the background, analyses the demands of original and new business based on choosing some typical business. By using principal component analysis (PCA), simplifies the affect system data of bandwidth prediction. Simultaneously, using RBM model based on deep learning predicts the bandwidth of power business requirement. It may give the reference for the next stage network construction of Power Company.

Copyright

© 2018, 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/).

Download article (PDF)

TY  - CONF
AU  - Dong Wang
PY  - 2018/04
DA  - 2018/04
TI  - Bandwidth Prediction for Business Requirement of Electric Power Communication Network with Deep-Learning
BT  - Proceedings of the 2018 3rd International Workshop on Materials Engineering and Computer Sciences (IWMECS 2018)
PB  - Atlantis Press
SP  - 521
EP  - 524
SN  - 2352-538X
UR  - https://doi.org/10.2991/iwmecs-18.2018.109
DO  - 10.2991/iwmecs-18.2018.109
ID  - Wang2018/04
ER  -