Immune optimization system based on immune recognition

被引：0

作者：

Cao, XB ^{[1
]}

Zhang, SH ^{[1
]}

Wang, XF ^{[1
]}

机构：

[1] Univ Sci & Technol China, Dept Comp Sci & Technol, Hefei 230026, Anhui, Peoples R China

来源：

8TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING, VOLS 1-3, PROCEEDING | 2001年

关键词：

immune recognition; gene recombination; negative selection; clonal selection;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Me propose an Immune Optimization System(IOS) based on immune recognition and implement its algorithm to solve practical optimization problems. The design of IOS is inspired by the negative selection and the clonal selection mechanisms in the biological immune system, which strategy is different from current optimization methods in that it gets good solutions through eliminating bad ones. This paper introduces in detail the basic principles of IOS and the implementation of corresponding algorithm, analyzes its ability and designs the experiments. The experiment results and theoretical analyses show that IOS has good ability of self-evolution and self-learning.

引用

页码：535 / 541

页数：7