自动化与信息工程2024，Vol.45Issue(3)：45-50,6.DOI:10.3969/j.issn.1674-2605.2024.03.007
基于匹配自主学习的网络信息识别与分类算法
Network Information Recognition and Classification Algorithm Based on Matching Autonomous Learning
摘要
Abstract
To improve the accuracy of network information recognition and classification,a network information recognition and classification algorithm based on matching autonomous learning is proposed to address the high dimensionality,high noise and other characteristics of massive network information.Firstly,using support vector machine to recognize network information;Then,a retrieval matrix is constructed using singular value decomposition algorithm for singular value decomposition and correlation queries;Finally,calculate the similarity matching degree of network information,and input the network information with higher matching degree into the convolutional neural network for learning and training,outputting the network information classification results.The experimental results show that the network information recognition accuracy of the algorithm reaches over 97.90%,and the average classification accuracy for different types of network information is 98.04%,which has certain practical application effectiveness.关键词
匹配自主学习/网络信息/支持向量机/奇异值分解/卷积神经网络/识别与分类Key words
matching autonomous learning/network information/support vector machine/singular value decomposition/convolutional neural network/recognition and classification分类
信息技术与安全科学引用本文复制引用
曾光辉..基于匹配自主学习的网络信息识别与分类算法[J].自动化与信息工程,2024,45(3):45-50,6.基金项目
2021年度广东省教育厅教育科学规划课题(高等教育专项)"教育信息化2.0背景下高职PAE翻转课堂教学模式研究"(2021GXJK613) （高等教育专项）
