Abstract
According to the principles of non-self detection and negative selection in natural immune system, two generating algorithms of detector are proposed in this paper after reviewing current detector generating algorithms used in artificial immune systems. We call them as Bit Mutation Growth Detector Generating Algorithm (BMGDGA) and Arithmetical-compliment Growth Detector Generating Algorithm (AGDGA) based on their operational features. The principle and work procedure of the two detector generating algorithms are elaborated in details in the paper. For evaluation of the proposed algorithms, they are tested and verified by using different datasets, and compared to Exhaustive Detector Generating Algorithm (EDGA). It turns out that the proposed two algorithms are superior to EDGA in detection performance and computational complexities.
This work was supported by the Natural Science Foundation of China with Grant No. 60273100.
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Tan, Y., Guo, Z. (2005). Algorithms of Non-self Detector by Negative Selection Principle in Artificial Immune System. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_122
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DOI: https://doi.org/10.1007/11539117_122
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