长沙理工大学学报（自然科学版）2016，Vol.13Issue(4)：90-96,7.
一种基于禁忌邻域的免疫网络分类算法
Atabooed neighborhood based immune network classification algorithm
摘要
Abstract
In order to improve memory cell determination scheme and the affinity represen-tation scheme in the immune classification algorithm,an immune network based classifica-tion algorithm is proposed.The algorithm adopts the training antigen’s tabooed neighbor-hood to guide the memory cells determination,and uses Gauss radial basis function to re-present the affinity between antibody-antigen.The algorithm is used for standard datasets classification,the classification performance shows that the search space is enlarged by in-troducing kernel function,and the taboo neighborhood based memory cell determination has significant optimal effect on maj ority problems.The results indicate that our algorithm is a high-performance classification algorithm and has potential ability for application.关键词
人工智能/人工免疫系统/免疫网络/禁忌邻域/分类Key words
artificial intelligence/artificial immune system/immune network/tabooed neighborhood/classification分类
信息技术与安全科学引用本文复制引用
邓泽林,刘宇,何锫..一种基于禁忌邻域的免疫网络分类算法[J].长沙理工大学学报（自然科学版）,2016,13(4):90-96,7.基金项目
湖南省科技计划项目(2015SK20463) （2015SK20463）
湖南省教育厅优秀青年项目(16B006) （16B006）
广东省自然科学基金资助项目(2015A030313501) （2015A030313501）
广东省普通高校创新团队建设项目(2015KCXTD014) （2015KCXTD014）
