Abstract. This paper describes an artiﬁcial immune system algorithm which implements a fairly close analogue of the memory mechanism proposed by Jerne(1) (usually known as the Immune Network Theory). The algorithm demonstrates the ability of these types of network to produce meta-stable structures representing populated regions of the anti gen space. The networks produced retain their structure indeﬁnitely and capture inherent structure within the sets of antigens used to train them. Results from running the algorithm on a variety of data sets are presented and shown to be stable over long time periods and wide ranges of parameters. The potential of the algorithm as a tool for multivariate data analysis is also explored.
|Number of pages||13|
|Publication status||Published - Sept 2003|
- data analysis
- network model
- artificial immune systems