吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

阴性选择算法检测器生成的优化及仿真

门洪, 陈鹏   

  1. 东北电力大学 自动化工程学院, 吉林 吉林 132012
  • 收稿日期:2013-12-17 出版日期:2014-11-26 发布日期:2014-12-11
  • 通讯作者: 陈鹏 E-mail:chenpeng16899199@126.com

RealValued Detector’s Generation of Negative Selection Algorithm: Optimization and Simulation

MEN Hong, CHEN Peng   

  1. School of Automation Engineering, Northeast Dianli University, Jilin 132012, Jilin Province, China
  • Received:2013-12-17 Online:2014-11-26 Published:2014-12-11
  • Contact: CHEN Peng E-mail:chenpeng16899199@126.com

摘要:

针对现有常规阴性选择算法在非我空间覆盖设计上未考虑自身免疫性检测器发生的问题, 提出一种能检测和剔除自身免疫性检测器的方法, 并以MATLAB软件为仿真实验平台, 分别对不规则分布数据、 环形分布数据和近圆形分布数据3种空间数据分布进行仿真研究. 仿真结果表明, 该方法能有效剔除90%的自身免疫性检测器, 提
升了免疫阴性选择算法的鲁棒性和自适应能力.

关键词: 人工免疫系统, 阴性选择, 自身免疫性检测器, 算法优化, 算法仿真

Abstract:

Since current conventional negative selection algorithm does not pay attention to the occurrence of autoimmune detector, and the presence of autoimmune detector will reduces the accuracy of fault diagnosis and other analogous areas, a method which can discover and eliminate pathogenicity detector was proposed. We specially designed a rule to detecting the presence of pathogenicity detector. With the help of MATLAB software, we simulated irregular dist
ributed selfdata, annulus distributed selfdata and nearly circle distributed selfdata. Results show that our method can effectively eliminate 90% of the pathogenic detector, enhance the robustness and adaptive ability of the immune negative selection algorithm.

Key words: artificial immune system, negative selection, autoimmune detector, algorithm optimization, algorithm simulation

中图分类号: 

  • TP18