作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2006, Vol. 32 ›› Issue (14): 184-186. doi: 10.3969/j.issn.1000-3428.2006.14.068

• 人工智能与识别技术 • 上一篇    下一篇

基于Rough集和支持向量机的作战飞机效能评估

高 尚   

  1. 江苏科技大学电子信息学院,镇江 212003
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2006-07-20 发布日期:2006-07-20

Assessing of Battle Plane Effectiveness Based on
Rough Set and Support Vector Machine

GAO Shang   

  1. School of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang 212003
  • Received:1900-01-01 Revised:1900-01-01 Online:2006-07-20 Published:2006-07-20

摘要: 简述了效能评估的各种方法,建立参数效能模型时,首先要挑选特征参数,采用知识约简方法选择武器的特征参数。利用支持向量机建立了参数效能模型,通过实例与指数法和神经网络法的结果进行了比较,结果表明支持向量机比较精确和简单。

关键词: 支持向量机, 效能, Rough集, 知识约简, 神经网络

Abstract: This paper discusses several methods for assessing the effectiveness.In weapon system analysis, the first place is to select the character parameters of weapon system. The character parameters of weapon system are selected based on reduction of knowledge. A parameter effectiveness model is established by using support vector machine. The method is illustrated through examples. The results obtained from support vector machine method are compared with that from index method and neural network method. The comparing results show that the support vector machine method is more accurate and simple than the index method and neural network method.

Key words: Support vector machine, Effectiveness, Rough set, Reduction of knowledge, Neural network