Brown, M., Gunn, S.R., Ng, C.Y. and Harris, C.J.
Neurofuzzy Systems Modelling: A Transparent Approach
Warwick, K. (eds.)
Dealing with Complexity: A Neural Network Approach.
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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.
|Venue - Dates:
||Dealing with Complexity: A Neural Network Approach, 1997-01-01
||Electronic & Software Systems, Southampton Wireless Group
||28 Oct 2001
||18 Apr 2017 00:24
|Further Information:||Google Scholar|
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