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Construction and Design of Parsimonious Neurofuzzy Systems

Record type: Conference or Workshop Item (Other)

Static fuzzy systems have been extensively applied in the Far East to a wide range of consumer products whereas researchers in the west have mainly been concerned with developing adaptive neural network that can learn to perform ill-defined, difficult tasks. Neurofuzzy systems attempt to combine the best aspects of each of these techniques as the transparent representation of a fuzzy system is fused with the adaptive capabilities of a neural network, while minimising the undesirable features. As such, they are applicable to a wide range of static, design problems and on-line adaptive modelling and control applications. This chapter focuses on how an appropriate structure for the rule base may be determined directly from a set of training data. It provides the designer with valuable qualitative information about the physics of the underlying process as well as improving the network's generalisation abilities and the condition of the learning problem.

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Citation

Bossley, K.M., Mills, D.J., Brown, M. and Harris, C.J., (1995) Construction and Design of Parsimonious Neurofuzzy Systems Hunt, K.J., Irwin, G.R. and Warwick, K. (eds.) At Neural Network Engineering in Control. , 153--177.

More information

Published date: 1995
Additional Information: Address: London
Venue - Dates: Neural Network Engineering in Control, 1995-01-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250144
URI: http://eprints.soton.ac.uk/id/eprint/250144
PURE UUID: f12dc862-4682-496e-9299-555df2d1bf98

Catalogue record

Date deposited: 04 May 1999
Last modified: 18 Jul 2017 10:43

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Contributors

Author: K.M. Bossley
Author: D.J. Mills
Author: M. Brown
Author: C.J. Harris
Editor: K.J. Hunt
Editor: G.R. Irwin
Editor: K. Warwick

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