摘要
针对通信网络故障诊断能力滞后,导致网络通信瘫痪,致使消息滞后等问题,提出通信网络故障识别系统,采用数字模拟技术和生成对抗网络算法(GAN)的优化组合来分析系统中实时存在的网络故障状况,利用数字模拟技术对真实物理数据进行交互,对通信网络数据进行虚拟化数据建模,将所获取的网络运行数据利用GAN算法进行分析处理,从而达到对网络进行故障识别的目的。试验结果表明,通过该系统技术检测出的数据精准度高达91.75%以上,表明该研究在通信网络故障识别的正确性。
In view of the time delay of communication network fault diagnosis,a communication network fault identification system is proposed.The optimized combination of digital simulation technology and GAN algorithm is used to analyze the real-time network fault conditions in the system.The digital simulation technology is used to store the real physical data interactively,and the communication network data are virtualized data modeling.The obtained network operation data are analyzed and processed using the generative adversarial network(GAN)algorithm,so as to achieve the purpose of network fault identification.The experimental results indicate that the accuracy of the data detected through this system technology is over 90%,indicating the correctness of this study in identifying communication network faults.
作者
罗鹏
李景文
LUO Peng;LI Jingwen(China Mobile Communications Corporation Guangxi Co.,Ltd.,Nanning 530022,China)
出处
《微型电脑应用》
2024年第3期198-201,213,共5页
Microcomputer Applications
关键词
数字模拟技术
GAN算法
数据建模
故障识别
digital analog technology
GAN algorithm
data modeling
fault identification
