计算机工程2011，Vol.37Issue(1)：173-174,177,3.DOI:10.3969/j.issn.1000-3428.2011.01.060
改进的克隆选择算法及其应用
Improved Clone Selection Algorithm and Its Application
常志英 1韩莉 1姜大伟1
作者信息
- 1. 东北电力大学自动化工程学院,吉林,吉林,132012
- 折叠
摘要
Abstract
In order to solve the existed problems that are the population size required to be determined by the experience, weaker multi-peak search capability and longer training time for Castro clone selection algorithm. It proposes a new immune clone selection algorithm based on real coding and adaptive zoom mutation method, which is able to dynamically determine the population size, owns strong global and local search capabilities and can search the global optimal points and possibly the greatest number of local extreme points. Simulation results show the improved algorithm to find the average running time and average number of peak points is obviously better than Castro clone selection algorithm, multimodal function optimization results are significantly improved.关键词
人工免疫系统/克隆选择/实数编码/自适应变焦变异Key words
artificial immune system/ clone selection/ real coding/ adaptive zoom mutation分类
信息技术与安全科学引用本文复制引用
常志英,韩莉,姜大伟..改进的克隆选择算法及其应用[J].计算机工程,2011,37(1):173-174,177,3.
