| Abstract |
In this study, we propose an optimized network information security evaluation GRA-BPNN model based on gray correlation analysis method combined with BP neural network model, and make corresponding optimization for network information security evaluation index. Simulation experiments are conducted to analyze the experimental model, and the simulation results show that the test sample values reach the best training performance at the 7th iteration after 13 iterations, and the R-values in the regression of training results all reach above 0.99, and the data are well-fitted. When the number of training iterations reaches 13, the training gradient is 0.00067928, the value of Mu is 0.001, and the validity test value is 6. The GRA-BPNN model scores 0.028 higher than the GRA method, which is in line with the expected error, and the higher score also proves that the GRA-BPNN model is more comprehensive and specific in its scoring consideration. © 2023 River Publishers. |
