Network safety accessment by least squares support vector machine classifier

摘要：

In order to solve the local optimum of BP neural network, least squares support vector machine (LSSVM) is proposed to access network safety in the paper.The least squares support vector machine classifier is used to solve the nonlinear classification problem in the network safety accessment,which can solve the quadric programming problem.which has the stronger classification ability than other prediction methods.The network safety accessment data are applied to study the superiority of least squares support vector machine. The comparison of network safety accessment between least squares support vector machine and BP neural network,which indicates that network safety accessment ability of least squares support vector machine is better than that of BP neural network.

关键词： network safety accessment least squares support vector machine classification

作者: Zhao Ling

作者单位: Northeast Petroleum University Daqing 163318,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Automation Engineering(ICCAE 2011)(2011年第三届IEEE计算机与自动化工程国际会议)

会议地点: 重庆

会议语种:英文

页码: 579-582

在线出版日期: 2011-01-21（万方平台首次上网日期，不代表论文的发表时间）