DC-STGCN: Dual-Channel Based Graph Convolutional Networks for Network Traffic Forecasting

DC-STGCN: Dual-Channel Based Graph Convolutional Networks for Network Traffic Forecasting

Network traffic forecasting is essential for efficient network management and planning. Accurate long-term forecasting models are also essential for proactive control of upcoming congestion events. Due to the complex spatial-temporal dependencies between traffic flows, traditional time series foreca...

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Bibliographic Details
Main Authors: Chengsheng Pan, Jiang Zhu, Zhixiang Kong, Huaifeng Shi, Wensheng Yang
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Electronics
Subjects:
network traffic forecasting
graph neural network
gated recurrent unit
spatiotemporal feature modeling
Online Access:https://www.mdpi.com/2079-9292/10/9/1014

Internet

https://www.mdpi.com/2079-9292/10/9/1014

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