P2.9.14 An artificial immune system model for gas sensors drift mitigation

2012 ◽  
Author(s):  
Gabriele Magna ◽  
Eugenio Martinelli ◽  
Alexandro Catini ◽  
Arnaldo D'Amico ◽  
Corrado Di Natale ◽  
...  
2013 ◽  
Vol 420 ◽  
pp. 311-317
Author(s):  
Gui Yang Li ◽  
Tao Guo

nspired by the theory of biological immune receptor editing/revision, an improved artificial immune system model is proposed. Different from generic model, the improved model does not need to set the detectors detection radius, but it gives the detector a certain degree of learning ability through receptor editing and receptor revision. This makes the detector has a capability to adjust the detection position and detection radius automatically. Experimental results show that the improved model achieves better detection performance than generic model.


2012 ◽  
Vol 616-618 ◽  
pp. 2166-2170
Author(s):  
Wei Wang ◽  
Chia Hung Wei ◽  
Yue Li ◽  
Li Wang

Recently, artificial immune system (AIS) inspired by the theory or immunology, has been developed rapidly and steadily. In this paper, we proposed an affinity based complex artificial immune system model considering the fact that the different eptitopes located on the surface of antigen can be recognized by a set of different paratopes expressed on the surface of immune cells. The experiment on trademark retrieval is performed to prove that the model proposed model has an excellent performance on retrieving the trademark images and outperforms the previously proposed algorithm.


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