Improved pattern recognition with artificial clonal selection?

J A White, S M Garrett

Research output: Chapter in Book/Report/Conference proceedingConference contribution

51 Citations (Scopus)


In this paper, we examine the clonal selection algorithm CLONALC and the suggestion that it is suitable for pattern recognition. CLONALC is tested over a series of binary character recognition tasks and its performance compared to a set of basic binary matching algorithms. A number of enhancements are made to the algorithm to improve its performance and the classification tests are repeated. Results show that given enough data CLONALG can successfully classify previously unseen patterns and that adjustments to the existing algorithm can improve performance

Original languageEnglish
Title of host publication Artificial Immune Systems
Subtitle of host publicationSecond International Conference, ICARIS 2003, Edinburgh, UK, September 1-3, 2003. Proceedings
EditorsJ Timmis, P Bentley, E Hart
Place of PublicationBerlin
Number of pages13
ISBN (Print)978-3-540-40766-9, 3-540-40766-9
Publication statusPublished - 2003
Event2nd International Conference on Artificial Immune Sysyems - EDINBURGH
Duration: 1 Sept 20033 Sept 2003

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2nd International Conference on Artificial Immune Sysyems


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