Negative Selection Algorithm

Optical combustion sensor data interpretation using hybrid negative selection algorithm with artificial immune networks

In most extended in Poland PC burners an individual air excess ratio rules an amount of pollution generated, yet there is a lack of method that allows measurement of output parameters. It is therefore necessary to use indirect methods, which could primarily include acoustic, and optical methods. These methods are non-invasive and can provide virtually not delayed and additionally spatially selective information about the combustion process but they are really difficult in interpretation.

Hybrid swarm negative selection algorithm for dna-microarray data classification

In the paper, a classification method is proposed. It is based on Combined Swarm Negative Selection Algorithm, which was originally designed for binary classification problems. The accuracy of developed algorithm was tested in an experimental way with the use of microarray data sets. The experiments confirmed that direction of changes introduced in developed algorithm improves its accuracy in comparison to other classification algorithms.