Studying computer communication networks to identify errors using enhanced neural network algorithms

Shangtao Zhang

doi:10.1117/12.3026712

15 March 2024 Studying computer communication networks to identify errors using enhanced neural network algorithms

Shangtao Zhang

Proceedings Volume 13075, Second International Conference on Physics, Photonics, and Optical Engineering (ICPPOE 2023); 130750M (2024) https://doi.org/10.1117/12.3026712
Event: Second International Conference on Physics, Photonics, and Optical Engineering (ICPPOE 2023), 2023, Kunming, China

Abstract

The stability and reliability of computer communication networks are crucial for the proper functioning of modern society. However, network faults are inevitable, so efficient fault detection systems are needed to quickly identify and solve problems. This study aims to improve the performance of network fault detection by introducing improved neural network algorithms and applying deep learning techniques to this field. First, we studied in detail the various types of faults that may occur in computer communication networks and constructed the corresponding fault datasets. Then, we introduced improved neural network structures, including convolutional neural networks and recurrent neural networks, to better capture the spatio-temporal characteristics of network data. Experimental results show that the improved neural network algorithm exhibits excellent performance in network fault detection. Compared with traditional methods, our model achieves significant improvements in detection rate and accuracy. In addition, the model demonstrates adaptability to different fault types, including traditional faults and emerging network threats. In summary, this study provides an efficient and reliable solution for fault detection in computer communication networks by introducing an improved neural network algorithm. This approach is expected to play an important role in real network operations and improve network stability and security, thus providing more reliable support for information communication in modern society.

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

Citation Download Citation

Shangtao Zhang "Studying computer communication networks to identify errors using enhanced neural network algorithms", Proc. SPIE 13075, Second International Conference on Physics, Photonics, and Optical Engineering (ICPPOE 2023), 130750M (15 March 2024); https://doi.org/10.1117/12.3026712

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KEYWORDS

Data modeling

Education and training

Convolution

Performance modeling

Neural networks

Computer networks

Convolutional neural networks

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