Hybrid Prediction Model for Passive Optical Network Traffic based on CEEMDAN and Machine Learning-Reference-Cited by-同舟云学术

Hybrid Prediction Model for Passive Optical Network Traffic based on CEEMDAN and Machine Learning

Published:2022-08-12 Issue: Volume: Page:
ISSN:
Container-title:2022 20th International Conference on Optical Communications and Networks (ICOCN)
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Author:

Xiao Wencai¹,Chen Zhe²,Liang Jiaqi¹,Xu Ou¹

Affiliation:

1. Institute of Advanced Photonics Technology, Guangdong University of Technology, School of Information Engineering,Guangzhou,China,510006

2. Guangdong University of Technology,GuangDong Provincial Key Laboratory of Information Photonics Technology,Guangzhou,China,510006

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9900493/9900919/09901194.pdf?arnumber=9901194

Reference12 articles.

1. Wireless traffic modeling and prediction using seasonal ARIMA models

2. Parsimonious Fitting of Long-Range Dependent Network Traffic Using ARMA Models

3. On the self-similar nature of Ethernet traffic (extended version)

4. PSO-SVR: A Hybrid Short-term Traffic Flow Forecasting Method;hu;2015 IEEE 21 st International Conference on Parallel and Distributed Systems (ICPADS),2015

5. Understanding data center traffic characteristics

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