Title :
The application of a coupled algorithm by the artificial immune and neural network
Author :
Zhou, Ying ; Zheng, Deling ; Qiu, Zhiliang
Author_Institution :
Inf. Eng. Sch., Beijing Univ. of Sci. & Technol., China
Abstract :
The paper presents an immune learning algorithm combining the artificial immune system (AIS) and the RBF neural network. The algorithm makes use of the characteristic by which the immune system can recognize various antigens and create an antibody memory to adjust the number and location of the centers of the hidden layer by regarding the input data of the network as antigens and the centers of the hidden layer as antibodies, and achieve the weights of the output layer by adopting the least squares algorithm. The algorithm is used for data clustering and recognition. The result shows that the algorithm possesses a good generalization ability and high recognition rate.
Keywords :
learning (artificial intelligence); least squares approximations; pattern classification; pattern clustering; radial basis function networks; RBF neural network; antibody memory; antigens; artificial immune system; coupled algorithm; data clustering; data recognition; immune learning algorithm; pattern classification; Artificial neural networks; Character recognition; Cloning; Clustering algorithms; Evolution (biology); Immune system; Least squares methods; Neural networks; Pathogens; Radial basis function networks;
Conference_Titel :
Communications, Circuits and Systems, 2004. ICCCAS 2004. 2004 International Conference on
Print_ISBN :
0-7803-8647-7
DOI :
10.1109/ICCCAS.2004.1346363
