基于矩阵形式的否定选择算法研究

现有的状态空间表示形式和匹配规则已经成为否定选择算法研究的瓶颈。为此，该文将状态空间从向量扩展到矩阵，提出了一种基于矩阵形式的否定选择算法。引入矩阵表示自我和非我空间，定义了元素匹配距离，在此基础上建立了双向匹配规则；同时根据状态空间特征建立了基于覆盖检验的检测器生成算法。实验结果表明该算法性能明显优于实值否定选择算法，有效解决了检测率和误报率联动的问题，且能产生更为高效的检测器。

Research on Negative Selection Algorithm Based on Matrix Representation

Due to the bottleneck of the current representation of the state space and match rule in the negative selection algorithm, a negative selection algorithm based on the matrix representation is presented, which extends the state space from the vector to the matrix. The elemental match distance is defined by introducing the matrix to denote self and nonself space, the bi-directional match rule is established. Moreover, a detector generating algorithm based on coverage rate testing is developed according to the characteristics of state space. The experimental results show that the proposed algorithm achieves better performance than the real-valued negative selection algorithm, and solves effectively the problem of the linkage of the detection rate and false rate. Furthermore, it is verified to generate more effective detectors.