关键词: 否定选择算法, 检测器, 实值, 非自体信息

Abstract: Aiming at the existing problems of negative selection algorithm, such as low detection rate and large detector set,?this paper proposes a new real-valued negative selection algorithm, which considers non-self information and twice move point, called NTMV-detector. This algorithm generates candidate detector center based on the training of non-self and the random method. The main idea of twice move point is: if the candidate detector center matches with mature detectors, it will move out of mature detector set, instead of giving up the detector center. Then, the algorithm adjusts the location of the detector center and determines detector radius through two closest self-data to the detector center. The experiments prove that this algorithm can effectively improve diagnosis rate and reduce misdiagnosis rate.

Key words: negative selection algorithm, detector, real-value, non-self information