Alagappan Viswanathan
Using orthogonal arrays to train artificial neural networks.
Viswanathan, Alagappan
Authors
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 |
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Deposit Date | Jun 5, 2009 |
Publicly Available Date | Jun 5, 2009 |
Keywords | Orthogonal arrays; Artificial neural networks; Taguchi methods |
Public URL | http://hdl.handle.net/10059/358 |
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VISWANATHAN 2005 Using orthogonal arrays to train
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Publisher Licence URL
https://creativecommons.org/licenses/by-nc-nd/4.0/
Copyright Statement
Copyright: the author and Robert Gordon University