Summary
Asia-Pacific Network Operations and Management Symposium
2016
Session Number:P1
Session:
Number:P1-28
A Multi-Applications Comprehensive Traffic Prediction Model for the Electric Power Data Network
Yu Zhou, Ningzhe Xing, Yutong Ji, Wenjing Li, Shaoyong Guo,
pp.-
Publication Date:2016/10/5
Online ISSN:2188-5079
Summary:
Currently, the requirements of service quality in the electric power data network are getting higher and higher, and traffic prediction is an important premise to promote service quality. In order to accurately predict the total traffic of communication channels, a Multi-Applications Comprehensive Traffic Prediction (MACTP) model is proposed in this paper. Differing from F-ARIMA and S-ARIMA models which are used to predict the traffic of single application, the proposed MACTP model is used to predict the traffic of multi-applications conveyed in the channels. Simulation results show that MACTP model has higher accuracy and efficiency than classical prediction models, and it is suitable for electrical power data network.