基于RBF神经网络的校园网络流量预测研究

Research on Campus Network Traffic Prediction Based on RBF Neural Networks

根据校园网网络流量的现状和特点,提出了基于RBF神经网络的校园网络流量预测模型。阐述了RBF神经网络的原理及学习方法,采集校园网的网络流量作为训练样本,利用RBF神经网络和Matlab仿真实验预测校园网网络流量未来的分布趋势,分析了预测结果。

According to the current situation and characteristics of campus network traffic, the prediction model of campus network traffic based on RBF neural network was proposed. First, the principle and learning method of RBF neural network were described;and the campus network traffic was collected to form the training sample. The distribution trend of campus network traffic was predicted by RBF neural network and Matlab simulation. The forecast results were briefly analyzed.