计算机科学 ›› 2013, Vol. 40 ›› Issue (12): 233-238.
李贵洋,郭涛
LI Gui-yang and GUO Tao
摘要: 被广泛采用的人工免疫系统模型ARTIS中的检测器没有主动学习能力,在具体应用中存在检测半径设定困难、检测性能低等问题,受生物免疫中受体编辑和免疫抑制的启发,提出了一种新的人工免疫系统模型REISAIS(Receptor Editing and Immune Suppression based Artificial Immune System),模型通过受体编辑分别 在耐受期和成熟期 赋予检测器一定的主动学习能力,从而提高了模型的检测率,而免疫抑制机制的引入则使得模型的误报率得到了有效控制。给出了模型中检测器和抑制器演化过程的形式化描述,对模型性能进行了分析,证明了受体编辑机制的引入在提高模型检测性能上的有效性。理论分析以及实验结果显示,与ARTIS模型相比,REISAIS模型无需设定检测半径并且检测性能更好。
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