Paper Title:
A Negative Selection Algorithm Based on Hierarchical Clustering of Self Set
  Abstract

In this article, we proposed a negative selection algorithm which based on hierarchical level cluster of self dataset CB-RNSA. First the self data set is clustered by different cluster radius, and then the self data are substituted by cluster centers to compare with candidate detectors to reduce the number of distance counting. In the detector creating process, the value of each detector property was restricted to a given value range so as to decrease the redundancy of detectors. The stimulation result shows that CB-RNSA is an effective algorithm for the creation of artificial immune detectors.

  Info
Periodical
Advanced Materials Research (Volumes 121-122)
Edited by
Donald C. Wunsch II, Honghua Tan, Dehuai Zeng, Qi Luo
Pages
486-489
DOI
10.4028/www.scientific.net/AMR.121-122.486
Citation
W. Chen, T. Li, X. J. Liu, Y. Q. Shi, "A Negative Selection Algorithm Based on Hierarchical Clustering of Self Set", Advanced Materials Research, Vols. 121-122, pp. 486-489, 2010
Online since
June 2010
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