Application of Improved CSA Algorithm-Based Fuzzy Logic in Computer Network Control Systems

In the past few years, with the high-speed popularization of computers and the widespread use of smart phones and mobile devices, the Internet has gradually become an indispensable part of people's daily lives. The Internet is constantly driving the process of digital society and providing people with more convenient and innovative applications. However, the internet industry also faces challenges such as runtime ambiguity, instability, large data volume, and difficulties in network situational awareness. In response to the above issues, this study combines the standard cuckoo algorithm with a fuzzy neural network to design a computer network situational awareness system. It uses principal component analysis to deduct the dimensions of the original data and then adds Gaussian noise to introduce appropriate randomness. The test proved that the improved model had a significant optimization effect on real network data, with an improvement of about 81.2% compared to the standard cuckoo algorithm. In the 220th iteration of the test set, the Loss function value was 0, which could accurately predict the network situation, with an accuracy rate of 98%. The designed system identification has higher recognition accuracy and less time consumption and has certain application potential in computer networks.

@article{Yu2024,
  title     = {Application of Improved CSA Algorithm-Based Fuzzy Logic in Computer Network Control Systems},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {8},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Jianxi Yu},
  doi       = {10.14569/IJACSA.2024.01508107},
  url       = {https://doi.org/10.14569/IJACSA.2024.01508107}
}