关键词: 人工免疫, 实值否定选择算法, 聚类分析, 自体区域

Abstract: Negative selection algorithm simply takes each self point and its vicinity as the self region.In this paper，real-valued negative selection algorithm is studied，the continuous self region is defined，the self data is classified to the self region through the means of cluster analysis，the partial training takes place at training stage according to the radius of self region and cosine distance with gravity of the self region，and in the self region V-detectors are deployed.Experimental results show that when the train self points are used together as a whole more information is provided，the boundary of self region can be probed，also efficiency of system and detection rate can be increased.

Key words: artificial immune system, real-valued negative selection algorithms, cluster analysis, self region