摘要
在对光纤通信网络环境进行检测时,由于受到外界环境干扰因素影响,检测结果的正确性和定位精度均无法满足实际要求,因此针对这一问题,在引入粒子群算法的基础上对其进行相关研究。通过对干扰信号进行检测,并提取其对应特征,基于粒子群算法的入侵干扰信号粒子群优化聚类,对存在的入侵干扰小信号进行定位和分离,提出一种全新的检测方法。通过实验证明了新的检测方法在实际应用中可以实现对入侵干扰信号的高精度和高正确率定位检测,进一步促进光纤通信网络运行质量的提升,使光纤通信网络得到更加广泛的应用。
When detecting the optical fiber communication network environment, due to the influence of external environmental interference factors, the correctness and positioning accuracy of the detection results cannot meet the actual requirements. Therefore,in order to solve this problem, the particle swarm algorithm is introduced on the basis of correlation. Research. By detecting the interference signal and extracting its corresponding characteristics, the intrusion interference signal particle swarm optimization clustering based on the particle swarm algorithm is used to locate and separate the existing intrusion interference signal, and a new detection method is proposed. Experiments have proved that the new detection method can achieve high-precision and high-accuracy location detection of intrusion interference signals in practical Applications, further promote the improvement of the operating quality of optical fiber communication networks, and make optical fiber communication networks more widely used.
作者
曹建生
CAO Jiansheng(Henan Polytechnic Institute,Nanyang Henan 473000,China)
出处
《信息与电脑》
2022年第1期186-188,共3页
Information & Computer
关键词
粒子群算法
网络入侵
干扰信号
particle swarm algorithm
network intrusion
interference signal
作者简介
曹建生(1978—),男,河南南阳人,硕士研究生,讲师。研究方向:电子技术、通信技术。
