Article

Immune clonal selection network

Authors:

Sun'an WangAuthors Info & Claims

AI'04: Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence

Pages 840 - 852

https://doi.org/10.1007/978-3-540-30549-1_72

Published: 04 December 2004 Publication History

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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.

References

[1]

Dasgupta, D., Forrest, S.: Artificial Immune Systems in Industrial Applications In: John, A M., Marcello, M.V (eds.): Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials, Vol 1 IEEE, Hawaii (1999) 257-267

Google Scholar

[2]

De Castro, L.N., Von Zuben, F.J.: The Clonal Selection Algorithm with Engineering Applications In: Whitley, D., Goldberg, D.E., Cantú-Paz, E., Spector, L., Parmee, I.C., Beyer, H (eds.): Proceedings of the Genetic and Evolutionary Computation Conference Morgan Kaufmann, Las Vegas (2000) 36-37

Google Scholar

[3]

Kim, J., Bentley, P.J.: Towards an Artificial Immune System for Network Intrusion Detection: an Investigation of Clonal Selection with a Negative Selection Operator In: IEEE Neural Networks Council (ed.): Proceedings of the 2001 Congress on Evolutionary Computation, Vol 2 IEEE, Seoul Korea (2001) 1244 -1252

Digital Library

Google Scholar

[4]

Dasgupta, D.: Artificial neural networks and artificial immune systems: similarities and differences In: Tien, J.M.(ed.):1997 IEEE International Conference on Computational Cybernetics and Simulation, IEEE, Orlando(1997) 873-878

Google Scholar

[5]

Hu X.C.: Comparison of Genetic Algorithm and Neural Network Technology http://www ics.hawaii.edu/~sugihara/research/.

Google Scholar

[6]

Lu, D.Y., Ma, B.L.: Modern Immunology Shanghai technology education publishing company, Shanghai (1998)

Google Scholar

[7]

Hagan, M.T., Demuth, H.B Beale, M.H.: Neural Network Design 1st edn China Machine Press, Beijing (2002)

Digital Library

Google Scholar

[8]

Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs 3rd edn Springer-Verlag, Berlin Heidelberg New York (1996)

Digital Library

Google Scholar

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Immune clonal selection network

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Information & Contributors

Information

Published In

AI'04: Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence

December 2004

1268 pages

ISBN:3540240594

Editors:
Geoffrey I. Webb
Faculty of Information Technology, Monash University, Australia
,
Xinghuo Yu
Faculty of Information Technology, Science, Engineering and Technology Portfolio, Royal Melbourne Institute of Technology, Melbourne, Australia

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 04 December 2004

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