Skip to main content

Research Repository

Advanced Search

Using orthogonal arrays to train artificial neural networks.

Viswanathan, Alagappan

Authors

Alagappan Viswanathan



Contributors

Grant M. Maxwell
Supervisor

Christopher Macleod
Supervisor

Ann Reddipogu
Supervisor

Abstract

The thesis outlines the use of Orthogonal Arrays for the training of Artificial Neural Networks. Such arrays are popularly used in system optimisation and are known as Taguchi Methods. The chief advantage of the method is that the network can learn quickly. Fast training methods may be used in certain Control Systems and it has been suggested that they could find application in disaster control, where a potentially dangerous system (for example, suffering a mechanical failure) needs to be controlled quickly. Previous work on the methods has shown that they suffer problems when used with multi-layer networks. The thesis discusses the reasons for these problems and reports on several successful techniques for overcoming them. These techniques are based on the consideration of the neuron, rather then the individual weight, as a factor to be optimised. The applications of technique and further work are also discussed.

Citation

VISWANATHAN, A. 2005. Using orthogonal arrays to train artificial neural networks. Robert Gordon University, MPhil thesis.

Thesis Type Thesis
Deposit Date Jun 5, 2009
Publicly Available Date Mar 28, 2024
Keywords Orthogonal arrays; Artificial neural networks; Taguchi methods
Public URL http://hdl.handle.net/10059/358
Award Date Oct 31, 2005

Files




Downloadable Citations