计算机技术与发展2012，Vol.22Issue(8)：75-77,81,4.
一种构造模糊隶属度的新方法
A New Method to Construct Fuzzy Membership
摘要
Abstract
The traditional fuzzy membership function of support vector machine is based on the distance between sample and the class center , it is unreasonable for irregular shape of data distribution. For the intrusion detection model based on rough set and fuzzy support vector machine , dig out the contribution which every condition attributes to decision attribute, propose a new design method of membership function based on weighted comparison between sample and the class center. The model using the method can reduce the geometry dependence of the sample set. It can effectively distinguish the sample points and noise points and outliers. Experimental results show that comparing with support vector machine and traditional fuzzy support vector machine, the fuzzy support vector machine with new membership function can achieve the best classification .and the new method is simple and fast.关键词
粗糙集/模糊支持向量机/模糊隶属度函数/入侵检测Key words
rough set/ fuzzy support vector machine/ fuzzy membership function/ intrusion detection分类
信息技术与安全科学引用本文复制引用
赵克楠,李雷,邓楠..一种构造模糊隶属度的新方法[J].计算机技术与发展,2012,22(8):75-77,81,4.基金项目
国家自然科学基金项目(61070234,61071167) （61070234,61071167）
江苏省高校自然科学基金项目(04KJB110097,08KJB520023) （04KJB110097,08KJB520023）
南京邮电大学攀登计划项目(NY207064) （NY207064）
