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. (eds.) 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
Venue - Dates: Dealing with Complexity: A Neural Network Approach, 1997-01-01
Organisations: Electronic & Software Systems, Southampton Wireless Group
ePrint ID: 250028
Date :
Date Event
1997Published
Date Deposited: 28 Oct 2001
Last Modified: 18 Apr 2017 00:24
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/250028

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