火力与指挥控制2017，Vol.42Issue(1)：54-57,4.
基于粗糙集和支持向量机的火炮内膛疵病识别方法
Study of Gun Bore Flaw Classification Method Based on Fuzzy Rough Set and Support Vector Machine
摘要
Abstract
Gun bore flaws intellective identification is final object of gun bore spying.It involves two aspects of feature extraction and flaw identification.In this paper,the gun bore flaw feature system which consists of shape,texture and color feature is built.Flaw identification sensitivity is analyzed based on fuzzy rough set,and the flaw feature dimensions are reduced by optimizing the flaw feature system.Using the small sample and non-linear data multi-classification organ of least-square support vector machine,the flaw identification efficiency and quality are heightened.关键词
火炮/内膛疵病/模糊粗糙集/支持向量机/疵病分类Key words
gun/bore flaw/support vector machine/fuzzy rough set/flaw classification分类
信息技术与安全科学引用本文复制引用
傅建平,雷洁,甘霖,王建仁..基于粗糙集和支持向量机的火炮内膛疵病识别方法[J].火力与指挥控制,2017,42(1):54-57,4.基金项目
军队科研计划基金资助项目 （）
