Vaccine-enhanced artificial immune system for multimodal function optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
International Journal of Artificial Intelligence and Soft Computing
Expert Systems with Applications: An International Journal
Artificial immune classifier with swarm learning
Engineering Applications of Artificial Intelligence
An adaptive knowledge evolution strategy for finding near-optimal solutions of specific problems
Expert Systems with Applications: An International Journal
An artificial immune classifier for credit scoring analysis
Applied Soft Computing
An adaptive artificial immune system for fault classification
Journal of Intelligent Manufacturing
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Current artificial immune system (AIS) classifiers have two major problems: 1) their populations of B-cells can grow to huge proportions, and 2) optimizing one B-cell (part of the classifier) at a time does not necessarily guarantee that the B-cell pool (the whole classifier) will be optimized. In this paper, the design of a new AIS algorithm and classifier system called simple AIS is described. It is different from traditional AIS classifiers in that it takes only one B-cell, instead of a B-cell pool, to represent the classifier. This approach ensures global optimization of the whole system, and in addition, no population control mechanism is needed. The classifier was tested on seven benchmark data sets using different classification techniques and was found to be very competitive when compared to other classifiers.