计算机科学 ›› 2010, Vol. 37 ›› Issue (1): 217-221.
• 人工智能 • 上一篇 下一篇
陶媛,吴耿锋,胡珉
出版日期:
发布日期:
基金资助:
TAO Yuan,WU Geng-feng,HU Min
Online:
Published:
摘要: 提出一种基于生物免疫系统工作原理的动态多目标人工免疫系统模型,模型由五元组—环境集、抗体集、抗原集、规则集和一个新的动态进化免疫算法DMEIA构成。DMEIA作为模型的核心元素,将进化算法保留上一代性相结合,用于控制和协调模型中其他元素的运作。仿真实验表明,DMEIA算法与已有算法相比,具有更稳定的环境追踪能力,以及良好的收敛性、多样性和解的分布性,从而验证了新模型的性能。
关键词: 动态多目标优化,进化免疫,环境追踪,克隆选择
Abstract: This paper proposed a new dynamic multi-object artificial immune system model based on simulating the principle of the biological immune system. The model consists of five elements, i. e. environment set, antibody set, antigen set, rule set and a Dynamic Multi-object Evolutionary Immune Algorithm(DMEIA). As a key clement of the model, DMEIA combines the feature of evolutionary algorithm which selects optimal non-dominated antibodies and makes them to join in evolution of next generation,and the characteristic of immune algorithm which has strong population diversity and adaptive searching ability to control and assorts with the operation of the model. Compared with the existed algorithms, DMEIA has better convergence, diversity, distribution of solution and stability of environment tracking, therefore the performance of the new model is proven to be available.
Key words: Dynamic mufti objective optimization, Evolutionary immune, Environment tracking, Clone selection
陶媛,吴耿锋,胡珉. 一种基于进化与免疫的动态多目标人工免疫系统模型[J]. 计算机科学, 2010, 37(1): 217-221. https://doi.org/
TAO Yuan,WU Geng-feng,HU Min. Dynamic Multi-object Artificial Immune System Model Based on Mechanisms of Evolution and Immunity[J]. Computer Science, 2010, 37(1): 217-221. https://doi.org/
0 / / 推荐
导出引用管理器 EndNote|Reference Manager|ProCite|BibTeX|RefWorks
链接本文: https://www.jsjkx.com/CN/
https://www.jsjkx.com/CN/Y2010/V37/I1/217
Cited