As an important part of data management, network traffic evaluation and prediction can not
only find network anomalies but also judge the future trends of the network. To predict …

Precise real-time traffic flow prediction is crucial for route guidance and traffic fine control.
With the development of autonomous driving, the mixed traffic flow state composed of …

Purpose The use of aviation incident data to carry out aviation risk prediction is of great
significance for improving the initiative of accident prevention and reducing the occurrence …

The anonymous system Tor uses an asymmetric algorithm to protect the content of
communications, allowing criminals to conceal their identities and hide their tracks. This …

The time-sensitive networking (TSN) working group standardizes time-aware shapes (TAS)
to reduce network latency, but the traditional TAS standard lacks adaptability and cannot …

Aiming at the nonlinearity and burstiness of network traffic in large cloud data centers, this
paper proposes a GAN-TrellisNet model to improve the accuracy of traffic prediction. Firstly …

Increasing the number of vehicles and their communications in smart cities is a critical issue
that leads to road and network traffic. Traffic prediction with high accuracy and less …

Abstract Retraction:[Yuanlong Cao, Keyang Gu, Junyi Wu, Xiang Zou, Lei Tao, Xin Huang,
Changgen Jiang, Anomaly detection with ensemble empirical mode decomposition and …

Stochastic configuration networks (SCNs), as a novel incremental generation model with
supervisory mechanism, has an excellent superiority in solving large-scale data regression …

Abstract QUIC (Quick UDP Internet Connections) proposed by Google is a new secure
general-purpose network transport protocol. Compared with TCP and TLS, QUIC combines …