Optimal feed-forward neural networks based on the combination of constructing and pruning by genetic algorithms

Author(s)
Author(s)
Wang, W. J.
Lu, W. Z.
Xu, Z. B.
Lo, S. M.
Wang, X. K.
Date Issued
2002
Publisher
IEEE
Related Publication(s)
Proceedings of the 2002 International Joint Conference on Neural Networks (IJCNN'02)
Start page
636
End page
641
Abstract
The determination of the proper size of an artificial neural network (ANN) is recognized to be crucial, especially for its practical implementation in important issues such as learning and generalization. In the paper, an effective design method of neural network architectures is presented. The network is firstly trained by a dynamic constructive method until the error is satisfied. The trained network is then pruned by genetic algorithm (GA). The simulation results demonstrate the advantages in generalization and expandability of the proposed method.
URI
DOI
SFU Affiliated Publication
No
Availability at SFU Library

No database links found.