基于粗糙集支持向量机的空袭目标识别OA北大核心CSCDCSTPCD
An Air Raid Target Recognition Based on Rough Set Support Vector Machine
为提高对空袭目标的识别能力,提出了一种基于粗糙集支持向量机的空袭目标识别方法.该模型用RS方法构建SVM数据处理系统的前置系统,充分利用RS理论在处理大数据量,消除冗余信息等方面的优势,减少了SVM训练数据,克服了SVM算法因为数据量太大而导致处理速度慢的缺点.根据分类识别的要求,在RS-SVM两类分类算法的基础上,建立了成对分类目标识别模型.通过仿真试验证明,该方法具有较高的识别率,在空袭目标识别中体现极强的优势.
In order to improve the ability of an air raid target recognition, a method of an air raid target recognition based on rough set support vector machine was proposed. The RS-method is advantage at processing big amount of data and removing redundancy information. So we take this method as the head system of the SVM data processing system to reduce SVM training data, therefore overcame the disadvantage of the SVM which is slow at processing big amount of data.…查看全部>>
王永成;王宏飞;姜长生
郑州航空工业管理学院,郑州450015南京航空航天大学,南京210016南京炮兵学院,南京211132
军事科技
粗糙集支持向量机目标识别
rough set,support vector machine,target recognition
《火力与指挥控制》 2011 (9)
133-135,3
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