| 基于独特型网络动力学模型的人工免疫算法 |
| |
| 引用本文： | 谭光兴,李中华,毛宗源.基于独特型网络动力学模型的人工免疫算法[J].华南理工大学学报(自然科学版),2006,34(1):62-65,72. |
| |
| 作者姓名： | 谭光兴 李中华 毛宗源 |
| |
| 作者单位： | 华南理工大学,自动化科学与工程学院,广东,广州,510640 |
| |
| 基金项目： | 广东省广州市科技攻关项目 |
| |
| 摘 要： | 针对传统人工免疫算法中相似度、浓度以及抗体现有评价方式存在的缺陷，采用独特型网络动力学模型，通过改进亲和力计算方法，使之综合表达函数值和抗体相似程度的信息，以抗体的浓度作为适应值，提出了一种基于独特型网络动力学模型的人工免疫算法．仿真结果表明，这种算法对多模态函数优化是有效的，其搜索效率及收敛速度均优于常见的人工免疫网络算法Opt—aiNet．
|
| 关 键 词： | 人工免疫算法 动力学模型 独特型网络 优化 |
| 文章编号： | 1000-565X（2006）01-0062-04 |
| 收稿时间： | 2005-03-07 |
| 修稿时间： | 2005-03-07 |
Artificial Immune Algorithm Based on Idiotypic-Network Dynamic Model |
| |
| Tan Guang-xing,Li Zhong-hua,Mao Zong-yuan.Artificial Immune Algorithm Based on Idiotypic-Network Dynamic Model[J].Journal of South China University of Technology(Natural Science Edition),2006,34(1):62-65,72. |
| |
| Authors: | Tan Guang-xing Li Zhong-hua Mao Zong-yuan |
| |
| Institution: | College of Automation Science and Engineering, South China Univ. of Tech. , Guangzhou 510640, Guangdong, China |
| |
| Abstract: | To overcome the demerits in evaluating the similarity, the concentration and the antibody of the conventional artificial immune algorithm, this paper proposes an improved artificial immune algorithm based on the idiotypic-network dynamic model by defining the antibody concentration as the fitness. In the proposed algorithm, the information about the function value and the similarity of antibody can be comprehensively extracted by modifying the calculation method of affinity. Simulated results show that the improved algorithm is effective on the optimization of multi-mode function and is of better searching efficiency and higher convergence speed than the conventional OptaiNet algorithm. |
| |
| Keywords: | artificial immune algorithm dynamic model idiotypic network optimization |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
