Abstract
In this article, based on our previous work CB-RNSA, we proposed an improved algorithm ICB-RNSA: using Principal Component Analysis (PCA) method to reduce data dimension in the data pre-treatment process; the distances between antigens are calculated by fractional norm distance to increase the detection discriminations. The experiment result shows that the efficiency and detection ability of ICB-RNSA are superior to CB-RNSA and other traditional negative selection algorithms.
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Chen, W., Li, T., Qin, J., Zhao, H. (2011). A New Cluster Based Real Negative Selection Algorithm. In: Qi, L. (eds) Information and Automation. ISIA 2010. Communications in Computer and Information Science, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19853-3_18
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DOI: https://doi.org/10.1007/978-3-642-19853-3_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19852-6
Online ISBN: 978-3-642-19853-3
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