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 Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Electronic & Software Systems
ePrint ID: 250028
Date Deposited: 28 Oct 2001
Last Modified: 27 Mar 2014 19:50
Publisher: Springer Verlag
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/250028

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