Mạng Miễn Dịch Nhân Tạo: Các Mô Hình và Ứng Dụng

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J. Suzuki and Y. Yamamoto, iNet: An extensible framework for simulating immune network. In Proc. of IEEE International Conference on Systems, Man, and Cybernetics, pp. 119–124 (2000).

J. Timmis, M. Neal, and J. Hunt, An artificial immune system for data analysis. BioSystems 55, pp.143–150 (2000).

J. Timmis, Artificial immune systems: a novel data analysis technique inspired by the immune network theory. Ph.D. Thesis, University of Wales, Aberystwyth, UK (2000).

G. B. Bezerra and L. N. de Castro, Bioinformatics data analysis using an artificial immune network. In Proc. of ICARIS. LNCS 2787, pp. 22–33 (2003).

L. N. de Castro and F. J. von Zuben, An evolutionary immune network for data clustering. IEEE SBRN, pp. 84–89 (2000).

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M. Neal, J. Hunt, and J. Timmis, Augmenting an artificial immune network. In Proc. of Int. Conf. on Systems and Man and Cybernetics, pp. 3821–3826 (1998).

T. Knight and J. Timmis, AINE: An immunological approach to data mining. In Proc. of IEEE International Conference on Data Mining, pp. 297–304 (2001).

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M. J. Neal, Meta-stable memory in an artificial immune network. In Proc. of the International Conference on Artificial Immune Systems, Edinburgh, UK, LNCS 2787, pp. 168–180. Springer (2003).

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L. N. de Castro and J. Timmis, An artificial immune network for multimodal function optimization, In Proc. of IEEE CEC, pp. 699–674 (2002).

L. N. de Castro and F. J. von Zuben, Learning and optimization using the clonal selection principle, IEEE Transactions on Evolutionary Computation (2001).

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L. N. de Castro and F. J. von Zuben, aiNET: An artificial immune network for data analysis. In Data Mining: A Heuristic Approach, H. A. Abbass, R. A. Saker, and C. S. Newton (eds.), Idea Group Publishing, Chapter XII, pp. 231–259.

M. Negoita, Artificial immune systems-An emergent technology for autonomous intelligent systems and data mining. AIS-ADM 2005, LNAI3505, pp. 19–36, 2005.

T. D. Do, S. C. Hui, and A. C. M. Fong, Artificial immune system for associative classification. ICNC 2005, LNCS 3611, pp. 849–858, 2005.

B. Alatas and E. Akin. Mining fuzzy classification rules using an artificial immune system with boosting. ADBIS 2005, LNCS 3631, pp. 283–293, 2005.

P. S. Andrews and J. Timmis. Inspiration for the next generation of artificial immune systems. LNCS 3627, pp. 126–138, 2005.

Z. Wu and Y. Liang. Self-regulation methods for model library based artificial immune systems. LNCS 3627, pp. 353–365, 2005.

H. Dai, Y. Yang, Y. Che, and Z. Tang. Clonal selection theory based artificial immune system and its application. LNCS 4233, pp. 1071–1078, 2006.

L. Wang, Y. Nie, W. Nie, and L. Jiao. Artificial immune strategies improve the security of data storage. ICNC 2005. LNCS 3611, pp. 839–848, 2005.

N. Tang and V. R. Vemuri. An artificial immune system approach to document clustering. SAC’05. March 2005

D. Dasgupta, K. KrishnaKumar, D. Wong, and M. Berry, Negative selection algorithm for aircraft fault detection. In Proc. of the Third International Conference on Artificial Immune Systems, Catania, Sicily, Italy, Sept. 2004.

J. Kim, W. O. Wilson, U. Aickelin, and J. McLeod. Cooperative Automated Worm Response and Detection ImmuNe ALgorithm (CARDINAL) inspired by T-cell immunity and tolerance. In Proc. of the Fourth International Conference on Artificial Immune Systems, Banff, Alberta, Canada. pp. 168–181, Aug. 2005.

Y. Cao and D. Dasgupta, An immunogenetic approach in chemical spectrum recognition. Chapter 36 in Advances in Evolutionary Computing (Ghosh & Tsutsui, eds.), Springer-Verlag, Inc. Jan. 2003.

A. Iqbal and M. A. Maarof, Towards danger theory based artificial APC model: Novel metaphor for danger susceptible data codons. In Proc. of the Third International Conference on Artificial Immune Systems, pp. 161–174, 2004.

S. Stepney, R. E. Smith, J. Timmis et al. Towards a conceptual framework for artificial immune systems. In Proc. of the Third International Conference on Artificial Immune Systems, pp. 53–64, 2004.

T. Oda and T. White. Immunity from spam: An analysis of an artificial immune system for junk email detection. In Proc. of the Fourth International Conference on Artificial Immune Systems, Banff, Alberta, Canada, pp. 276–289, Aug. 2005.

M. Neal. Meta-stable memory in an artificial immune network. In Proc. of the 2nd International Conference on Artificial Immune Systems Springer, pp.168–180, 2003

Z. Liu, X. Jin, R. Bie, and X. Z. Gao. FAISC: a Fuzzy Artificial Immune System Clustering Algorithm. In Proc. of the Third International Conference on Natural Computation, pp. 657–661, 2007.