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dc.contributor.author Neal, Mark
dc.date.accessioned 2006-03-16T15:39:14Z
dc.date.available 2006-03-16T15:39:14Z
dc.date.issued 2002
dc.identifier.citation Neal , M 2002 , ' An artificial immune system for continuous analysis of time-varying data ' pp. 76-85 . en
dc.identifier.other PURE: 66220
dc.identifier.other dspace: 2160/34
dc.identifier.uri http://hdl.handle.net/2160/34
dc.identifier.uri http://www.aber.ac.uk/~icawww/Proceedings/toc-icaris.htm en
dc.description M. Neal, An Artificial Immune System for Continuous Analysis of Time-Varying Data, in Proceedings of the 1st International Conference on Artificial Immune Systems (ICARIS), 2002, eds J Timmis and P J Bentley, volume 1, pages 76-85, en
dc.description.abstract This paper presents an artificial immune system (AIS) which produces artificial immune networks that are meaningful, of a bounded size and dynamic over a very large number of data presentations. This behaviour had proved elusive up to this time but has now permitted the application of the AIS to situations requiring continuous learning. It also removes the need to decide when to stop training an AIS. The new version of the algorithm is described, and results are presented for analysis of static and dynamic versions of a trivial two-dimensional data set and Fisher’s Iris data. It is argued that the changes made from previous versions of the “resource limited” algorithm are in keeping with the goals of remaining true to the immune system analogy and making the system as simple as possible. en
dc.format.extent 10 en
dc.language.iso eng
dc.relation.ispartof en
dc.subject network model en
dc.subject immunology en
dc.subject artificial immune systems en
dc.subject memory en
dc.title An artificial immune system for continuous analysis of time-varying data 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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