基于GA-BP神经网络的网络流量预测研究

In the era of booming satellite network development, network traffic prediction technology plays a crucial role in managing and planning satellite network resources, ensuring service quality, and enhancing network security. This paper explores the problem of network traffic prediction within the context of satellite network architecture, aiming to improve the accuracy and efficiency of traffic prediction to support satellite network routing decisions. The study primarily focuses on the traffic reception of individual satellite nodes as the basis for conducting traffic prediction research. This paper employs a BP neural network for prediction and introduces a genetic algorithm to optimize the BP neural network. The experimental results demonstrate that the GA-BP neural network performs better in traffic prediction. Compared to the BP neural network, the GA-BP neural network reduces the average absolute error, root mean square error, and average relative error by 11.663%, 6.574%, and 5.400%, respectively.?????