Neurofuzzy Systems Modelling: A Transparent Approach
Brown, M., Gunn, S.R., Ng, C.Y. and Harris, C.J. (1997) Neurofuzzy Systems Modelling: A Transparent Approach. In, Warwick, K. (ed.) Dealing with Complexity: A Neural Network Approach. , Springer Verlag.
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Description/Abstract
This chapter advocates a cyclic construction approach to data modelling based on a design-train-validate-interpret cycle. Traditional approaches to data modelling with neural networks typically produce opaque systems which are difficult to interpret and hence validate. Neurofuzzy systems equip neural networks with a linguistic interpretation which provides the designer with enhanced transparency enabling the loop to be closed in the modelling cycle. Three neurofuzzy construction algorithms are discussed, and their performances are evaluated on two real data sets.
| Item Type: | Book Section |
|---|---|
| Additional Information: | Address: London |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control Faculty of Physical and Applied Science > Electronics and Computer Science > Electronic & Software Systems |
| Item ID: | 250028 |
| Date Deposited: | 28 Oct 2001 |
| Last Modified: | 02 Mar 2012 12:38 |
| Contributors: | Brown, M. (Author) Gunn, S.R. (Author) Ng, C.Y. (Author) Harris, C.J. (Author) Warwick, K. (Editor) |
| Date: | 1997 |
| Additional Information: | Address: London |
| Status: | Published |
| Publisher: | Springer Verlag |
| Further Information: | Google Scholar |
| URI: | http://eprints.soton.ac.uk/id/eprint/250028 |
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