一种基于受体编辑的实值阴性选择算法

摘要

受生物免疫受体编辑理论的启发,提出了一种基于受体编辑的实值阴性选择算法RERNS(Receptor Editinginspired Real Negative Selection Algorithm).对于匹配自体的检测器,该算法采用定向受体编辑使之获得新生,而这些新生的检测器分布在自体与非自体的边界区域,从而增加了检测器的多样性,并改善了算法对边界区域的覆盖情况；对于不匹配自体的检测器,该算法采用识别相同最近自体的定向受体编辑,使检测器在包含原检测范围的情况下扩大了对非自体空间的覆盖.理论分析和实验验证表明,与实值阴性选择算法中具有代表性的RNS算法和V-detector算法相比,RERNS算法生成的未成熟检测器更少,且检测性能更好.%Inspired by theory of biological immune receptor editing,a receptor editing-inspired real negative selection al-gorithm(RERNS) was proposed. For the detector that matches self,algorithm uses directional receptor editing to make a new life. These new detectors are located in the area of self and non-self boundary, thereby the diversity of detector is increased and the boundary covered by the algorithm is also improved. For the detector that does not match self, algorithm uses direction receptor editing for identifying identical nearest self to expand coverage of no-self space under the circumstances of containing original scope of detector. Theoretical analysis and experimental verification show that RERNS algorithm generates less un-mature detectors and obtains better detection performance than the most representative RNS algorithm and V-detector algorithm.