兵工自动化2025，Vol.44Issue(5)：37-41,51,6.DOI:10.7690/bgzdh.2025.05.009
基于电网协同业务场景的数据全链路检测研究
Research on Data Full Link Detection Based on Power Grid Collaboration Business Scenario
谢辉 1司福利 1张建中 1郑景立 1张继英 1陈飞云 1张沛2
作者信息
- 1. 南方电网数字电网研究院有限公司,广州 510000
- 2. 天津弘源慧能科技有限公司,天津 300308
- 折叠
摘要
Abstract
Based on deep learning,a fully connected neural network-decision tree algorithm is designed for intrusion detection of full data link in power grid collaborative business scenarios.This paper analyzes the causes of the problems in the power grid collaborative business scenario,and introduces the common classification algorithms.It combines the fully connected neural network in deep learning with the decision tree algorithm in machine learning,and obtains the designed fully connected neural network-decision tree intrusion detection algorithm model.Through the test on the relevant data,the detection accuracy of the model in network intrusion can reach 0.99,the precision can reach 0.984,the recall rate is 0.97,and the F1 score is 0.977.The results show that compared with similar algorithms,the proposed algorithm has outstanding advantages,provides more accurate technical support for the full data link in the grid collaborative business scenario,and plays an important role in the optimization of power grid planning.关键词
电网协同业务/全链路/入侵检测/电网规划/决策树/全连接神经网络Key words
power grid collaborative business/full link/intrusion detection/power grid planning/decision tree/fully connected neural network分类
动力与电气工程引用本文复制引用
谢辉,司福利,张建中,郑景立,张继英,陈飞云,张沛..基于电网协同业务场景的数据全链路检测研究[J].兵工自动化,2025,44(5):37-41,51,6.
