Abstract
Based on the Antibody Clonal Selection Theory of immunology, the general steps of ICSA (Immune Clonal Selection Algorithm) are presented in this paper. The network framework of ICSA is put forward, and the dynamic characters of ICSA are analyzed based on the Lyapunov theory. Then, this paper gives a novel Artificial Immune System Algorithm, Pseudo- Grads Hybrid Immune Clonal Selection Network (GHICSN). The simulation results of some functions optimization indicate that GHICSN improves the performance of ICSA to some extent.
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Du, H., Jin, X., Zhuang, J., Jiao, L., Wang, S. (2004). Immune Clonal Selection Network. In: Webb, G.I., Yu, X. (eds) AI 2004: Advances in Artificial Intelligence. AI 2004. Lecture Notes in Computer Science(), vol 3339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30549-1_72
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DOI: https://doi.org/10.1007/978-3-540-30549-1_72
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