Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The paper presents the concept of the ship immune system. The task of the system mentioned is to differentiate self objects, i.e. objects that are not dangerous to our ship, from other objects that can be a potential threat. To perform the task the system uses mechanisms adapted from artificial immune systems. Since, the traditional model of artificial immune system assumes objects represented in the form of binary strings, in the paper modifications to this model are proposed. The modifications mentioned either makes it possible to represent objects in the form of real valued vectors or transform real valued representations to simpler binary or integer ones.
Wydawca
Czasopismo
Rocznik
Tom
Strony
101--107
Opis fizyczny
Bibliogr. 11 poz., rys., tab.
Twórcy
autor
- Polish Naval Academy
Bibliografia
- [1] Balthrop J., Esponda F., Forrest S., Glickman M. Coverage and Generalization in Artificial Immune System. in Proc. Genetic Evolutionary Computation Conf., 2002.
- [2] Butz M. V. Rule-based Evolutionary Online Learning Systems: Learning Bounds, Classification, and Prediction. University of Illinois, IlliGAL Report No. 2004034, 2004.
- [3] D’haeseleer P., Forrest S., Helman P. An Immunological Approach to Change Detection: Algorithms, Analysis and Implications, Scientific Literature Digital Library - http://citeseer.ist.psu.edu
- [4] Esponda F., Forrest S., Helman P. A Formal Framework for Positive and Negative Detection Schemes. IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics, 34(1), pp. 357-373, 2004.
- [5] Goldberg D. E. Genetic algorithms in search, optimization and machine learning. Addison Wesley, Reading, Massachusetts. 1989.
- [6] Hightower R., Forrest S., Perelson A. The Baldwin Effect in the Immune System: Learning by Somatic Hypermutation. In R. K. Belew and M. Mitchell, editors, Individual Plasticity in Evolving Populations: Models and Algorithms. Addison-Wesley, pp. 159-167, 1996.
- [7] Hofmeyr S., Forrest S., Somayaji A. Intrusion Detection using Sequences of System Calls, Scientific Literature Digital Library - http://citeseer.ist.psu.edu
- [8] Holland J. H. Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, Michigan. 1975.
- [9] Forrest S., Hofmeyr S. Immunology as Information Processing, Design Principles for Immune Systems and Other Distributed Autonomous Systems, eds. Oxford Univ. Press, pp. 361-387, 2000
- [10] Praczyk T., Detection of self navigational aids on radar image using ideas from immune systems, Archives of Control Science, Volume 17(LIII), No. 3, pages 241-259, 2007
- [11] Praczyk T., Adaptation of r-contiguous-bits scheme borrowed from immune systems to characteristic points of radar image identification, Theoretical and Applied Informatics, vol. 19(2007), pp. 37-56, 2007
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BATA-0011-0027