计算机与数字工程2019，Vol.47Issue(7)：1688-1693,6.DOI:10.3969/j.issn.1672-9722.2019.07.026
融合PCA降维的改进深度神经网络工控安全算法
Improved Neural Network Industrial Safety Algorithm Integrated of PCA Dimension Reduction Computer Engineering and Applications
刘庆华 1吴昊天1
作者信息
- 1. 江苏科技大学计算机学院 镇江 212000
- 折叠
摘要
Abstract
In order to improve the security and anti-interference ability of industrial control system,this paper proposes an im?proved industrial neural network defense method based on the PCA dimension reduction and the improved deep neural network. Firstly,the proposed method reduces the dimensionality of the industrial data using the dimension reduction theory of principal com?ponent analysis(PCA). Then the deep neural network extracts the features of the network. Finally,the softmax classifier classifies industrial data. Experiment results show that compared with unintegrated algorithm,this method achieves higher recognition accura?cy and has great application potential.关键词
工业控制系统/深度神经网络/PCA/adagradKey words
industrial control system/deep neural network/PCA/adagrad分类
信息技术与安全科学引用本文复制引用
刘庆华,吴昊天..融合PCA降维的改进深度神经网络工控安全算法[J].计算机与数字工程,2019,47(7):1688-1693,6.
