所属单位：

理学院

发表刊物：

Proceedings 2010 3rd IEEE International Conference on Broadband Network & Multimedia Technology

关键字：

中文关键字：网络流量;新陈代谢GM(1,1);神经网络;预测模型，英文关键字：Network Traffic;metabolic-GM(1,1);Neural Network;F

摘要：

For the method of neural network can modify and better the forecasting effects of grey prediction model, a combined NN-GM (1,1) forecasting model is proposed. After the time sequence of the network traffic was analyzed, the equidistant metabolic GM (1,1) forecasting model was constructed, and the residual error of the model was corrected by neural network based on Error Back propagation (BP) algorithm. The forecasting results of the experiments and the simulation show that the combined model is more effective than the single common grey model. The application of the proposed combined model to network traffic forecasting may offer scientific rationale for LAN virus detection, illegal invasion prevention and Internet routing decision.

备注：

白燕

合写作者：

马珂

第一作者：

任庆昌,白燕

论文类型：

期刊论文

卷号：

卷：

期号：

期：

页面范围：

页：191-194

是否译文：

否

发表时间：

2010-10-01