J4 ›› 2015, Vol. 42 ›› Issue (2): 84-88.doi: 10.3969/j.issn.1001-2400.2015.02.014

• 研究论文 • 上一篇    下一篇



  1. (1. 西安电子科技大学 电路CAD研究所,陕西 西安 710071; 2. 西安工业大学 电子信息工程学院,陕西 西安 710032; 3. 西安电子科技大学 计算机学院,陕西 西安 710071)
  • 收稿日期:2013-12-10 修回日期:2014-02-12 出版日期:2015-04-20 发布日期:2015-04-14
  • 通讯作者: 苗苗
  • 作者简介:苗苗(1981-),女,西安电子科技大学博士研究生,E-mail:mmiao1107@gmail.com.
  • 基金资助:

Linear classification method based on the electromagnetism-like mechanism algorithm

MIAO Miao1,2;JIANG Jianguo3   

  1. (1. Research Inst. of Electronic CAD, Xidian Univ., Xi'an 710071, China; 2. School of Electronic Information Engineering, Xi'an Technological Univ., Xi'an 710032, China; 3. School of Computer Science and Technology, Xidian Univ., Xi'an 710071, China)
  • Received:2013-12-10 Revised:2014-02-12 Online:2015-04-20 Published:2015-04-14
  • Contact: MIAO Miao

摘要: 根据最优超平面和类电磁机制算法的思想,提出了一种组合优化线性分类方法.该方法利用样本训练提取样本个体的类别特征,寻找到将类别分类的最优超平面,设计并实现了一种采用改进的类电磁机制算法的组合优化线性分类方法.试验取得了很好的分类效果,证实了组合优化线性分类方法的可行性.

关键词: 组合优化, 线性分类, 类电磁机制算法, 类别特征, 样本训练

Abstract: Because of the characteristics that the linear classifier can be easily extended to nonlinear one, it becomes one of the most commonly used methods in statistical pattern recognition. According to the optimal hyperplane and Electromagnetism-like mechanism algorithm, a combinational optimization linear classification algorithm is proposed, The new algorithm extracts category features from individual samples by sample training, finds the optimal classification hyperplane, designs and realizes a combinational optimization linear classification algorithm based on the improved Electromagnetism-like mechanism algorithm. Experiments show that the algorithm has good classification results, confirm the feasibility of combinational optimization linear classification algorithm.

Key words: combinational optimization, linear classification, electromagnetism-like mechanism algorithm, category feature, sample training


  • 中图分类号:TP301.6