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Peer-to-Peer Networking and Applications
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08-02-2024

A new method of network traffic prediction based on combination model

Authors: Guohao Li, Zhongda Tian

Published in: Peer-to-Peer Networking and Applications | Issue 3/2024

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Abstract

The article introduces a hybrid model for network traffic prediction that combines the ARIMA model for linear components and BiLSTM for nonlinear components, optimized using an improved Particle Swarm Optimization (IPSO) algorithm. The IPSO algorithm enhances the optimization of the BiLSTM hyperparameters, leading to higher prediction accuracy and lower error rates. The method is validated through extensive experiments on real-world network traffic data, demonstrating its superior performance over existing models. The proposed ARIMA-IPSO-BiLSTM model provides a robust solution for efficient network operation, resource allocation, and anomaly detection, contributing to the future design of network management strategies.
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Metadata
Title
A new method of network traffic prediction based on combination model
Authors
Guohao Li
Zhongda Tian
Publication date
08-02-2024
Publisher
Springer US
Published in
Peer-to-Peer Networking and Applications / Issue 3/2024
Print ISSN: 1936-6442
Electronic ISSN: 1936-6450
DOI
https://doi.org/10.1007/s12083-024-01630-0

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