Research on improved algorithms for network performance prediction based on grey prediction model

Qinghua Chen; Bei Hong; Xuepeng Jiang; Jiaojiao Gu

doi:10.1117/12.3009422

11 October 2023 Research on improved algorithms for network performance prediction based on grey prediction model

Qinghua Chen, Bei Hong, Xuepeng Jiang, Jiaojiao Gu

Author Affiliations +

Proceedings Volume 12918, Fourth International Conference on Computer Science and Communication Technology (ICCSCT 2023); 1291809 (2023) https://doi.org/10.1117/12.3009422
Event: International Conference on Computer Science and Communication Technology (ICCSCT 2023), 2023, Wuhan, China

Abstract

With the rapid development of computer networks, the scale of networks has become extremely large and complex, and a slight fluctuation in network performance parameters may have an impact on the entire network service, which makes accurate prediction of network performance particularly important. In this paper, an improved grey prediction model is applied to the prediction of network performance, and a Markov residual correction model is used to correct the prediction results to improve the prediction accuracy. The experimental results show that the error between the predicted and actual values after Markov residual correction is significantly reduced compared with the traditional grey prediction model, and the results are closer to the actual situation.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qinghua Chen, Bei Hong, Xuepeng Jiang, and Jiaojiao Gu "Research on improved algorithms for network performance prediction based on grey prediction model", Proc. SPIE 12918, Fourth International Conference on Computer Science and Communication Technology (ICCSCT 2023), 1291809 (11 October 2023); https://doi.org/10.1117/12.3009422

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