Artificial Intelligence Helps Computer Network Fault Diagnosis and Optimization
Studying and applying artificial intelligence techniques to solve the accuracy problem of computer network error diagnosis and optimize network performance, a core problem. Six algorithms to solve four major problems (physical connection errors, configuration errors, network overload errors, security attack errors) for network error detection and optimization have been investigated and explained. After the experimental verification, an improved support vector model in this study can recognize physical connection errors with just 0.24 seconds and a security attack error of 5.35 seconds. This result not only confirms the effectiveness and accuracy of artificial intelligence techniques in network diagnostics but also provides a new optimization strategy for network operation that contributes to the stability and security of network services.
Authors
- Yaling Zhang (ORCID: https://orcid.org/0000-0002-7122-0268)
- Xiaojun Li (ORCID: https://orcid.org/0000-0002-6275-8808)
- Jeffrey Cheng (ORCID: https://orcid.org/0000-0003-3674-7301)
- Xiande Zhuo
Institutions
- Chengdu Medical College (CN)
- Chengdu University (CN)
- Inner Mongolia University of Technology (CN)
Publication Details
- Published
- 2025-06-06
- DOI
- https://doi.org/10.1109/icicke65317.2025.11136357
- Citations
- 1
- Primary Topic
- Software System Performance and Reliability
- Type
- article
- Field-Weighted Citation Impact
- 1.49