摘要
提出了一种人工免疫识别算法.该算法将所识别的数据作为抗原,利用抗体、抗原的亲和作用,通过刺激/抑制有关抗体的活动建立一个抗体记忆集合,识别和表示数据结构组织,它具有识别多样性、自我调节功能等特点.通过对二维实数空间的数据和Iris数据进行实验,结果表明该方法聚类效果好,识别率高,且具有较好的泛化能力.
An artificial immune recognition algorithm is proposed. Inspired by the metaphor of the interaction of antibodies with antigens, it processes the data as antigens, and then gets an antibody memory matrix by inspiring or restraining the activity of antibodies. The ability of data recognition and data structure description can be achieved by the memory matrix. The algorithm has the characteristics of recognition variety and self-adjustment. The experiment results demonstrate that the algorithm has good clustering effect and high recognition rate on R2 space data and iris data.
出处
《北京科技大学学报》
EI
CAS
CSCD
北大核心
2004年第4期438-441,共4页
Journal of University of Science and Technology Beijing
基金
高校博士点专向科研基金资助项目(No.20020008004)
关键词
免疫识别
亲和作用
抗体记忆
识别率
Algorithms
Antigen
antibody reactions
Antigens
Data description
Immunology
