A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2003; you can also visit the original URL.
The file type is application/pdf.
Improved Pattern Recognition with Artificial Clonal Selection?
[chapter]
2003
Lecture Notes in Computer Science
Preserved Fulltext
In this paper, we examine the clonal selection algorithm CLONALG and the suggestion that it is suitable for pattern recognition. CLONALG 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
doi:10.1007/978-3-540-45192-1_18
fatcat:n76oqhxulnftdkleevqs3bivtu