Gaussian Process Regression Ensemble Model for Network Traffic Prediction

Gaussian Process Regression Ensemble Model for Network Traffic Prediction

Network traffic prediction is substantial for network optimization and resource management. However, designing an efficient predictive model considering different traffic characteristics, including periodicity, nonlinearity, and nonstationarity, is challenging. Recently, ensemble learning is attract...

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Bibliographic Details
Main Authors: Abdolkhalegh Bayati, Kim-Khoa Nguyen, Mohamed Cheriet
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Network traffic prediction
machine learning
ensemble learning
Gaussian process regression (GPR)
Dirichlet process (DP) clustering
Online Access:https://ieeexplore.ieee.org/document/9204965/

Internet

https://ieeexplore.ieee.org/document/9204965/

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