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Castro, L.N. and Von Zuben, F.J. 2000. An evolutionary immune network for data clustering. – IEEE Brazilian Symposium on Artificial Neural Networks. pp 84-89.
Castro, L.N. and Timmis, J. 2002. Artificial immune systems; a new computational approach. – Springer-verlag. London, UK.
Castro L.N. and Von Zuben, F.J. 2000. The clonal selection algorithm with engineering applications. –GECCO 2000, Genetic and Evolutionary Computation Conference 36-37.
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Graaff, A.J. and Engelbrecht, A.P. 2006. Optimised coverage of non-self with evolved lymphocytes in an artificial immune system. – Int. J. Comp. Intel. Res. 2: 127-150.
Heckerman, D.A. 1996. Tutorial on learning with Bayesian networks. Technical report. – MSR-TR. 95-96.
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Kim, J. and Bentley, P.J. 1999. Negative selection and niching by an artificial immune system for network intrusion detection. – GECCO 1999, Genetic and Evolutionary Computation Conference, pp 149-158.
Kim, J. and Bentley, P.J. 2002. Immune memory in the dynamic clonal selection algorithm. – 1st International Conference on Artificial Immune Systems, pp 59-67.
Nasraoui, O., Dasgupta, D. and Gonzalez. 2002. The promise and challenges of artificial immune system based web usage mining. – Second International Conference on Data Mining. pp 29-39.
Pearl, J. 1990. Bayasian network, UCLA, CL.
Rasoulzadeh, M., Golmakani, N., Ebrahimzadeh, Zagmi, S. and Nasiri, S. 2017. Cranberry Effects on Prevention of Urinary Tract Infection. – J. St. Res. Comm. Sabzevar Univ. Med. Sci. 22: 16-22.
Sarafijanovic, S. and Le Boudec, J. 2004. An artificial immune system for misbehavior detection in mobile ad-hoc networks with virtual thymus. – 3st International Conference on Artificial Immune Systems, pp 342-356. [
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Twycross, J. 2007. Integrated innate and adaptive artificial immune systems applied to process anomaly detection. – Ph.D. thesis, School of Computer Science. University of Nottingham, UK.
