移动通信网络异常信号优化识别研究  

Mobile Communication Network Anomaly Signal Optimization Identification Study

作　　者：张涛[1] 张颖江[1] 

机构地区：[1]湖北工业大学信息技术中心,湖北武汉430068

出　　处：《计算机仿真》2017年第3期309-312,共4页Computer Simulation

摘　　要：对移动通信网络异常信号进行准确识别,可以提高移动通信网络运行的安全性。进行异常信号识别时,需要提取移动通信网络异常信号数据特征,对根据特征对异常信号数据进行分类,建立移动通信网络异常信号识别模型,而传统基于遗传神经网络算法,是通过对大量的网络信号样本信息进行训练及测试实现的,不能对异常信号数据特征进行准确提取,存在识别不准确、误差大的问题。提出基于DFI的移动通信网络异常信号的识别方法。将DFI技术与SVM算法相融合,引入到移动通信网络异常信号的识别分类问题中,获取移动通信网络异常信号数据的特性,利用SVM算法建立移动通信网络异常信号最优分类面,构建移动通信网络异常信号识别模型,基于SVM的控制模块,对移动通信网络异常信号进行识别控制。仿真结果表明,提出的移动通信网络异常信号识别模型具有较高的识别准确度。This article proposes a method for identifying abnormal signals in mobile communication networks based on DFI.We combined the DFI technology with SVM algorithm,and introduced it into identification and classification of abnormal signals to obtain characteristic of abnormal signal data.The SVM algorithm was used to establish optimal classification face of abnormal signal.A mobile recognition model for abnormal signal was built to control and identify it based on control module of SVM.Simulation results show that the proposed model has higher recognition accuracy.

关 键 词：移动通信网络 异常信号识别 最优分类面 

分 类 号：TP393.06[自动化与计算机技术—计算机应用技术]