Title :
Genetic algorithm based self-growing training for RBF neural networks
Author :
Bai, Yungei ; Zhang, L.
Author_Institution :
Sch. of Electron. & Electr. Eng., Leeds Univ., UK
fDate :
6/24/1905 12:00:00 AM
Abstract :
Presents a RBF self-growing algorithm for training the RBFNN. The GA is employed to assist the search for the optimal RBFNN structure. The output layer weights are trained using a RLMS scheme with a dynamic learning rate
Keywords :
genetic algorithms; learning (artificial intelligence); least mean squares methods; radial basis function networks; RBF neural networks; RLMS scheme; dynamic learning rate; genetic algorithm based self-growing training; least mean square learning rule; optimal structure; output layer weights; radial basis function neural networks; search; training technique; Clustering algorithms; Genetic algorithms; Joining processes; Multi-layer neural network; Multilayer perceptrons; Neural networks; Neurons; Pattern classification; Radial basis function networks; Vectors;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1005583
