基于海明距离的阴性选择算法的改进*

作者：张宇，周喜川，沈海斌 日期：2007-10-24/span> 浏览：4308 查看PDF文档

基于海明距离的阴性选择算法的改进*

张宇，周喜川，沈海斌
（浙江大学 电气工程学院，浙江 杭州 310027）

摘要：阴性选择算法是人工免疫系统的核心算法之一，有效检测器数量与“黑洞”数量是采用阴性选择算法的系统所必须关注的两个要素。在分析连续r位匹配规则与海明距离匹配规则的基础上，提出了一种基于海明距离的阈值自适应阴性选择算法。相对于传统的连续r位匹配算法，该算法具有检测器数目小，“黑洞”空间小的优点。实验结果表明，新算法大幅降低了有效检测器的数量，并通过阈值的自适应性有效地降低了“黑洞”数量。
关键词：人工免疫系统；阴性选择算法；海明距离；匹配阈值；黑洞
中图分类号：TP301文献标识码：A文章编号：1001-4551(2007)09-0001-04

Improvement of negative selection algorithm based on hamming distance
ZHANG Yu, ZHOU Xichuan, SHEN Haibin
(College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)
Abstract: Negative selection algorithm is one of core algorithm of artificial immune system, the quantity of effective detectors and holes are two element of the system using negative select algorithm. A threshold adjustable negative algorithm was presented, which was based on continuous r bits matching rule and hamming distance matching rule. This new algorithm reduces the number of effective detectors and holes, which are inevitable in negative selection algorithm. Experimentations based on this algorithm show that the new algorithm reduces the number of detectors and holes dramatically.
Key words: artificial immune system; negative selection algorithm; hamming distance; threshold of matching; hole

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