Immune Optimization System Based on Immune Recognition

摘要：

We 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.

关键词： Immune Recognition Gene Recombination Negative Selection Clonal Selection.

作者: Cao Xianbin Zhang Sihai Wang Xufa

作者单位: Department of Computer Science and Technology University of Science and Technology of China HeFei, AnHui 230026

会议类型: 国际会议

会议名称: 8th International Conference on Neural Information Processing(ICONIP 2001)(第八届国际神经信息处理大会)

会议地点: 上海

会议语种:英文

页码: 573-579

在线出版日期: 2001-11-14（万方平台首次上网日期，不代表论文的发表时间）