基于支持向量机的电力数据通信流量数字化监测方法
Digital Monitoring Method of Power Data Communication Traffic Based on Supported Vector Machine
王娜 1代永春 1衡江2
作者信息
- 1. 国网武威供电公司,甘肃武威 733000
- 2. 国网武威市凉州区供电公司,甘肃武威 733000
- 折叠
摘要
电力数据通信网络承载着电力系统的关键业务数据,其安全稳定运行至关重要.针对日益严峻的网络安全形势,文章提出一种基于支持向量机的电力数据通信流量数字化监测方法.该方法通过特征提取、模型训练、异常检测等环节,实现了对海量通信流量数据的智能分析与精准识别.仿真实验结果表明,该方法能够有效发现网络中的各类异常行为,检测准确率高达98.5%,为保障电力系统的安全稳定运行提供有力支撑.
Abstract
Power data communication network carries the key business data of power system,and its safe and stable operation is very important.In view of the increasingly severe network security situation,this paper proposes a digital monitoring method of power data communication traffic based on support vector machine.This method realizes intelligent analysis and accurate identification of massive communication traffic data through feature extraction,model training,anomaly detection and other links.The simulation results show that this method can effectively find all kinds of abnormal behaviors in the network,and the detection accuracy is as high as 98.5%,which provides a strong support for ensuring the safe and stable operation of the power system.
关键词
电力通信网络/流量监测/支持向量机Key words
power communication network/traffic monitoring/support vector machine引用本文复制引用
出版年
2024
NETL
NSTL
万方数据