E3S Web Conf.
Volume 213, 20202nd International Conference on Applied Chemistry and Industrial Catalysis (ACIC 2020)
|Number of page(s)||4|
|Section||Energy Mining Research and Composite Material Performance Analysis|
|Published online||01 December 2020|
Research and Application of Hybrid Adaptive Forecasting Method Based on SOA
Hunan University of Information Technology School of Electronic Information
* Corresponding author: firstname.lastname@example.org
The current network security situation is becoming more and more severe. In order to improve the accuracy of network security situation prediction, a network security situation prediction method based on crowd search algorithm optimized BP neural network is proposed. This algorithm uses the four characteristics of egoism, altruism, pre-action and uncertain reasoning unique to the crowd search algorithm to determine the search strategy, finds the best fitness individual, obtains the optimal weights and thresholds, and then performs random initialization of the BP neural network The threshold and weight are assigned, and the predicted value is obtained after neural network training. Finally, it is compared with the predicted value obtained by the other two optimization algorithms. Experiments show that the algorithm used in network security situation prediction has higher accuracy, smaller errors, and better stability.
© The Authors, published by EDP Sciences, 2020
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