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dc.contributor.author Neal, Mark
dc.date.accessioned 2006-03-16T15:44:51Z
dc.date.available 2006-03-16T15:44:51Z
dc.date.issued 2003-09
dc.identifier.citation Neal , M 2003 , ' Meta-stable memory in an artificial immune network ' pp. 168-180 . en
dc.identifier.other PURE: 66242
dc.identifier.other dspace: 2160/35
dc.identifier.uri http://hdl.handle.net/2160/35
dc.identifier.uri http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2787&spage=168 en
dc.description Neal, M., Meta-stable memory in an artificial immune network, Proceedings of the 2nd International Conference on Artificial Immune Systems {ICARIS}, Springer, 168-180, 2003,LNCS 2787/2003 en
dc.description.abstract Abstract. This paper describes an artificial immune system algorithm which implements a fairly close analogue of the memory mechanism proposed by Jerne(1) (usually known as the Immune Network Theory). The algorithm demonstrates the ability of these types of network to produce meta-stable structures representing populated regions of the anti gen space. The networks produced retain their structure indefinitely and capture inherent structure within the sets of antigens used to train them. Results from running the algorithm on a variety of data sets are presented and shown to be stable over long time periods and wide ranges of parameters. The potential of the algorithm as a tool for multivariate data analysis is also explored. en
dc.format.extent 13 en
dc.language.iso eng
dc.relation.ispartof en
dc.subject data analysis en
dc.subject network model en
dc.subject immunology en
dc.subject artificial immune systems en
dc.title Meta-stable memory in an artificial immune network en
dc.type Text en
dc.type.publicationtype Conference paper en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Intelligent Robotics Group en
dc.description.status Non peer reviewed en


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