Title :
A Novel Classification Method Based on Artificial Immune System and Quantum Mechanics Theory
Author :
Ma, Liling ; Zhang, Zhao ; Zhou, Xiaohang ; Wang, Junzheng
Author_Institution :
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
Abstract :
Inspired by natural immune systems, Artificial Immune System (AIS) is an emerging kind of computational intelligence paradigm. The traditional immune algorithm and Ai-net for clustering still have the problems of training time-consumption and accuracy. In this paper, AIS Algorithm is improved with Quantum Mechanics theory and the Schro¿dinger equation to add the idea of the energy level into the immune net. The analysis and simulation data are taken from UCI data. It is proved that the accuracy of the artificial immune system is improved, while gaining better training speed compared with the one with border methods such as SVM at the same degree of precision.
Keywords :
artificial immune systems; pattern clustering; quantum theory; support vector machines; AIS algorithm; artificial immune system; pattern clustering; quantum mechanics theory; support vector machines; Analytical models; Artificial immune systems; Clustering algorithms; Computational intelligence; Computational modeling; Data analysis; Energy states; Equations; Immune system; Quantum mechanics; artificial immune system; clustering; computational intelligence; energy level; quantum mechanics theory;
Conference_Titel :
Computational Intelligence and Security, 2009. CIS '09. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5411-2
DOI :
10.1109/CIS.2009.138