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Neurofuzzy Model Construction for the Modelling of Non-linear Processes

Bossley, K.M., Brown, M. and Harris, C.J. (1995) Neurofuzzy Model Construction for the Modelling of Non-linear Processes At 3rd European Control conference. , 2438--2443.

Record type: Conference or Workshop Item (Other)

Abstract

Neurofuzzy systems are ideal for modelling nonlinear processes; combining the transparent knowledge representation of fuzzy systems with the well established learning techniques of associative memory networks. In the control community there is a need for high-dimensional modelling, but unfortunately these neurofuzzy systems suffer from the curse of dimensionality. To make the use of high-dimensional neurofuzzy systems practical, off-line construction algorithms need to be developed which generate parsimonious models. This need for off-line construction algorithms is enhanced by the lack of expert knowledge from which models are traditionally developed. This paper outlines the concepts of B-spline neurofuzzy systems and presents several representations which can be exploited to produce parsimonious models. Finally, an off-line construction algorithm based on several of these representations is illustrated with a simple example.

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More information

Published date: 1995
Additional Information: Address: Rome, Italy
Venue - Dates: 3rd European Control conference, 1995-01-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250234
URI: http://eprints.soton.ac.uk/id/eprint/250234
PURE UUID: c6801b51-75bb-4fc7-b54c-57ac0f95518c

Catalogue record

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

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Contributors

Author: K.M. Bossley
Author: M. Brown
Author: C.J. Harris

University divisions

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