A Novel Classification Method Based on Artificial Immune System and Quantum Mechanics Theory

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.