Negative-selection algorithm of mutation search in self space to train detector
采用在自己空间变异搜索来训练检测器的阴性选择算法

To overcome the defects of the present negative-selection algorithm in fault detection, based on self-space, abnormity detection algorithm was improved. It trained detector according to the mutation mechanism of genetic algorithm and the principle of vaccine inoculation and clone selection. The simulation shows that under the precondition that the improved algorithm can generally cover the self-space, its computing complexity dramatically declines while its fault detecting efficiency greatly improves.