Computer and Modernization ›› 2022, Vol. 0 ›› Issue (12): 42-49.

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Reliability Evaluation Model of BP Neural Network Based on Particle Swarm Optimization


  1. (College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)
  • Online:2023-01-04 Published:2023-01-04

Abstract: The reliability of the CPU is critical to a computer system. For the problem that the difficulty of parameter optimization and inaccurate evaluation accuracy in reliability analysis and evaluation of methods such as neural network, this paper proposes a reliability evaluation model based on particle swarm optimization BP neural network. The model optimized the PSO algorithm optimized by the sine map, and then optimized the weights and thresholds of the BP neural network. Through this method, the weights and thresholds of the BP neural network were optimized. Based on the reliability of each functional module in the CPU, a reliability evaluation model of the CPU was established according to the improved BP neural network model. The reliability evaluation of the CPU was completed through model training and testing. Through comparative experiments, the validity and accuracy of the model for CPU reliability evaluation under radiation environment are verified.

Key words: CPU, reliability evaluation, PSO Algorithm, BP neural network,  , soft errors