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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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
|Date Deposited:||28 Oct 2001|
|Last Modified:||27 Mar 2014 19:50|
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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