DocumentCode
2955311
Title
A Novel Immune Algorithm for Supervised Classification Problem
Author
Li, Xiaoming
Author_Institution
Modern Educ. Center (MEC), HeNan Radio & Telev. Univ., Zhengzhou, China
fYear
2011
fDate
30-31 July 2011
Firstpage
1
Lastpage
4
Abstract
This article presents a novel immune algorithm for a solution of supervised classification problem .The algorithm is based on the risk model, the use of dangerous and hazardous signal mechanism, the risk by assessing the Antigen to the signal classification; and use of antibody-Antigen interactions learning mechanisms to make antibodies have strong populations of adaptive learning capacity. Simulation results show that the algorithm have good classification results and learning performance compared with other traditional algorithm.
Keywords
artificial immune systems; learning (artificial intelligence); pattern classification; adaptive learning capacity; antibody-antigen interactions learning mechanisms; dangerous signal mechanism; hazardous signal mechanism; immune algorithm; learning performance; risk model; signal classification; supervised classification problem; Classification algorithms; Cloning; Complexity theory; Data models; Immune system; Joining processes; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation and Systems Engineering (CASE), 2011 International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4577-0859-6
Type
conf
DOI
10.1109/ICCASE.2011.5997726
Filename
5997726
Link To Document