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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

Record type: Book Section


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.

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Published date: 1997
Additional Information: Address: London
Venue - Dates: Dealing with Complexity: A Neural Network Approach, 1997-01-01
Organisations: Electronic & Software Systems, Southampton Wireless Group


Local EPrints ID: 250028
PURE UUID: 505f9d02-5ced-48d8-93d4-01dff2fe0fc1

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Date deposited: 28 Oct 2001
Last modified: 18 Jul 2017 10:44

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Author: M. Brown
Author: S.R. Gunn
Author: C.Y. Ng
Author: C.J. Harris
Editor: K. Warwick

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