An Improved Detector Set Generation Mechanism in Negative Selection Algorithm

Abstract

in view of the shortcomings of the detector generation mechanism in the existing negative selection algorithm, a new method of boundary detection is proposed to deal with the problem of the boundary dilemma. In the algorithm, it is used as the self region of the body and its adjacent points. The realization process and advantages of the algorithm are given. The algorithm is validated by the synthetic data set 2DSyntheticData and the actual Iris data set and the Biomedical data set. Experimental results show that the detection rate of this algorithm is high, especially the points that are in the self and non self boundary can be detected effectively.