进化策略用于阴性选择算法  

Application of Evolutionary Strategy to Negative Selection Algorithm

作　　者：肖赤心[1,2] 蔡自兴[1] 王勇[1] 刘星宝[1] 

机构地区：[1]中南大学信息科学与工程学院,湖南长沙410083 [2]湘潭大学信息工程学院,湖南湘潭411105

出　　处：《小型微型计算机系统》2008年第11期2091-2094,共4页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(60234030,60404021)资助;国家基础研究基金项目(A1420060159)资助;湖南省院士基金项目(08IJY3035)资助

摘　　要：提出一种基于(μ+λ)进化策略的阴性选择算法;构造匹配信噪比方法综合运用海明规则和r位连续匹配规则,使检测器分布更均匀;同传统的阴性选择算法相比,进化机制使得检测器的搜索不再盲目.对于较大规模的自体集也可以快速准确生成成熟检测器.数值实验表明新算法产生成熟检测器的迭代次数、黑洞数量均大幅下降,同时检测率显著提高.A new negative selection algorithm based on （μ＋λ）-ES is proposed. Assembling the Hamming and r-continuous match rules with the signal-to-noise ratio method, detectors of the whole system are distributed more even. Compared with the traditional negative selection algorithm, the new algorithm is no longer blindness in searching mature detectors for the evolutionary strategy. Especially for the case on large-scale self, the new algorithm can generate the mature detectors rapidly and accurately also. The results obtained show that both the number of iteration to generate mature detectors and the number of holes decline quickly,while the rate of detecting abnormity raises.

关 键 词：阴性选择 进化策略 信噪比 检测器 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]