This study attempts to propose a novel algorithm, hybrid of artificial immune network (aiNet) and particle swarm K-means optimization (PSKO)(aiNet-PSKO) algorithm, for cluster analysis. In order to verify the proposed methods, four benchmark data sets, Iris, Glass, Wine, and Breast Cancer, are first employed. The computational results indicate that aiNet-PSKO algorithm outperforms artificial im...

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system, providing the initial detection of pathogenic invaders. Research into this family of cells has revealed that they perform information fusion which directs immune responses. We have derived a Dendritic Cell Algorithm based on the functionality of these cells, by modelling the bio...

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system, providing the initial detection of pathogenic invaders. Research into this family of cells has revealed that they perform information fusion which directs immune responses. We have derived a Dendritic Cell Algorithm based on the functionality of these cells, by modelling the bio...

We propose an immune system inspired Artificial Immune System (AIS) algorithm for the purposes of automated program verification. It is proposed to use this AIS algorithm for a specific automated program verification task: that of predicting shape of program invariants. It is shown that the algorithm correctly predicts program invariant shape for a variety of benchmarked programs. Program invar...

This paper presents an artificial immune system (AIS) which produces artificial immune networks that are meaningful, of a bounded size and dynamic over a very large number of data presentations. This behaviour had proved elusive up to this time but has now permitted the application of the AIS to situations requiring continuous learning. It also removes the need to decide when to stop training a...

One of the most important artificial immune algorithms is negative selection algorithm, which is an anomaly detection and pattern recognition technique; however, recent research has shown the successful application of this algorithm in data classification. Most of the negative selection methods consider deterministic boundaries to distinguish between self and non-self-spaces. In this paper, two...

The amount of online transactions is growing these days to a large number. A big portion of these transactions contains credit card transactions. The growth of online fraud, on the other hand, is notable, which is generally a result of ease of access to edge technology for everyone. There has been research done on many models and methods for credit card fraud prevention and detection. Artificia...