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A Combined Network Traffic Prediction Method Based on Ensemble Empirical Mode Decomposition

A technology of ensemble empirical mode and network flow, which is applied in the field of combined network flow forecasting based on ensemble empirical mode decomposition, can solve problems such as non-adaptiveness and difficulty in selecting wavelet bases for wavelet transform decomposition layers

Active Publication Date: 2022-02-22
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, wavelet transform has the problem of determining the number of decomposition layers and choosing wavelet bases, which depends on specific signal characteristics and application fields, and is not self-adaptive.

Method used

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  • A Combined Network Traffic Prediction Method Based on Ensemble Empirical Mode Decomposition
  • A Combined Network Traffic Prediction Method Based on Ensemble Empirical Mode Decomposition
  • A Combined Network Traffic Prediction Method Based on Ensemble Empirical Mode Decomposition

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Embodiment Construction

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0042] The present invention provides a combined network traffic prediction method based on ensemble empirical mode decomposition, such as figure 1 ,include:

[0043] S1: Obtain raw traffic data and perform preprocessing;

[0044] S2: Decompose the network traffic into IMF components with a single frequency on different time scales through ensemble empirical mode decomposition;

[0045] S3: Determine the stationarity of the IMF component through autocorrelat...

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Abstract

The invention belongs to the technical field of network traffic forecasting, and particularly relates to a combined network traffic forecasting method based on ensemble empirical mode decomposition, including: obtaining original traffic data and performing preprocessing; decomposing network traffic into different The IMF component with a single frequency on the time scale; through autocorrelation and partial autocorrelation analysis, determine the stationarity of the IMF component; predict the smooth IMF component with a linear ARMA model; use the nonlinear Elman neural network for the non-stationary IMF component Network prediction; summing the predicted values ​​of each IMF component to obtain the predicted value of network traffic; the invention describes and predicts actual network traffic more accurately and comprehensively, thereby improving prediction accuracy and increasing prediction reliability.

Description

technical field [0001] The invention belongs to the technical field of network traffic forecasting, in particular to a combined network traffic forecasting method based on ensemble empirical mode decomposition (Empirical Mode Decomposition, EMD). Background technique [0002] In recent years, with the rapid development of the Internet industry, the network scale has become increasingly large and the network structure has become increasingly complex, and network management is facing great challenges. Improving network operation efficiency through an efficient network management mechanism is an important topic for network management workers. [0003] In the face of increasingly complex network interconnection environments and increasing network traffic, researchers and scholars need to use more resources and time to monitor and analyze these network traffic conditions to deal with unexpected situations of network congestion and congestion. to ensure good network quality. Tra...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L41/147H04L41/14H04L41/142H04L43/0876
Inventor 唐宏姚立霜刘丹王云峰裴作飞
Owner CHONGQING UNIV OF POSTS & TELECOMM
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