An Improved Immune Network Regulation Algorithm

Author

Yu, Ying

Author_Institution

Dept. of Autom., Commun. Univ. of China, Beijing

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

4337

Lastpage

4341

Abstract

The discrimination of antibodies against antigens is one of the two basic tasks of antibodies in computer immune systems. The other is the maintenance of equilibrium and stability of the antibodies system. During the process of the discrimination, to decrease the redundancy well as keep the balance of antibodies, this paper have proposed an improved immune network regulation algorithm based on the immune memory and diversity. The activation and suppression are mainly based on the degree of the discrimination of antibody against antigen in the improved algorithm. Experimental results show that the improved algorithm is characterized by better decrease of redundancy in the emergence of antigen

Keywords

artificial intelligence; security of data; antibody discrimination system; artificial immune system; computer immune system; idiotypic immune network theory; immune network regulation algorithm; Artificial immune systems; Artificial intelligence; Automation; Biology computing; Competitive intelligence; Computer networks; Cybernetics; Electronic mail; Immune system; Machine learning; Machine learning algorithms; Stability; Systems biology; Artificial Immune Systems; computer immune system; idiotypic immune network; immune concentration;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.259081

Filename

4028836