Fault and handling measures of computer network communication technology based on deep learning

Xun Li; Lulu Chang; Yong Chen

doi:10.1117/12.3046055

17 October 2024 Fault and handling measures of computer network communication technology based on deep learning

Xun Li, Lulu Chang, Yong Chen

Author Affiliations +

Proceedings Volume 13289, International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024); 1328910 (2024) https://doi.org/10.1117/12.3046055
Event: The International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024), 2024, Hangzhou, China

Abstract

In order to improve the security and efficiency of computer network communication, this article analyzes the application of deep learning technology in network communication fault detection and processing. By introducing convolutional neural networks and long short-term memory networks, research focuses on network fault prediction, feature extraction, and security reinforcement. The results indicate that combining these technologies can significantly improve the stability and security protection capabilities of the network, providing effective improvement strategies for network communication technology.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xun Li, Lulu Chang, and Yong Chen "Fault and handling measures of computer network communication technology based on deep learning", Proc. SPIE 13289, International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024), 1328910 (17 October 2024); https://doi.org/10.1117/12.3046055

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