DocumentCode
2030979
Title
A Clustering Model Inspired by Humoral Immunity
Author
Tian Yuling ; Ren Peng
Author_Institution
Coll. of Comput. & software, Taiyuan Univ. of Technol., Taiyuan
fYear
2009
fDate
23-24 May 2009
Firstpage
1
Lastpage
4
Abstract
In biological immune system, B-cells secrete large numbers of antibodies to recognize and eliminate the antigens. Inspired by the relationship of B-cells and antibodies, an effective immune model is presented in this paper. As its learning capability, this model can recognize not only the existing antigens but also the antigens that are unknown. The structure of the model and the detailed algorithm are given in this paper. And the validity of the model is proved through an experiment of motor fault data clustering.
Keywords
artificial immune systems; learning (artificial intelligence); pattern clustering; B-cells; antibodies; antigens; biological immune system; clustering model; humoral immunity; learning capability; Biological system modeling; Biology computing; Cells (biology); Cloning; Clustering algorithms; Data mining; Detectors; Educational institutions; Immune system; Plasmas;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-3893-8
Electronic_ISBN
978-1-4244-3894-5
Type
conf
DOI
10.1109/IWISA.2009.5072611
Filename
5072611
Link To Document