Research on fuzzy neural network algorithms for nonlinear network traffic predicting  

作　　者：WANG Zhao-xia SUN Yu-geng ZHANG Qiang QIN Juan SUN Xiao-wei SHEN Hua-yu 

机构地区：[1]School of Electrical Engineering and Automation, Tianjin University, Tian）in 300071, Ohina [2]Department of Opto-Electronic Information and Electronic Engineering, Tianjin Institute of Technology, Tianjin 300191,China [3]Deparlment of Communication and Information Engineering, Guilin University of Electronic Technology, Guilin 541004, China

出　　处：《Optoelectronics Letters》2006年第5期373-375,共3页光电子快报（英文版）

基　　金：This workis supportedin part by China Postdoctoral Foundationunder grant (2005037529) ,Tianjin High Education Science De-velopment Foundation under grant (20041325) and Education Ministry Doctoral Discipline Foundation of China under grant(2003005607) .

摘　　要：This paper addresses the use of fuzzy neural networks （FNN） for predicting the nonlinear network traffic. Through training the fuzzy neural networks with momentum back-propagation algorithm （MOBP） and choosing the appropriate activation function of output node, the traffic series can be well predicted by these structures. From the effective forecasting results obtained, it can be concluded that fuzzy neural networks can be well applicable for the traffic series prediction. In addition,the performance of the FNN was particularly discussed and analyzed in terms of prediction ability compared with solely neural networks. The effectiveness of the oroBosecl FNN is demonstrated through the simulation.

关 键 词：模糊神经网络算法 非线性网络 网址 动量 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]