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Fuzzy connectives as a combination tool in a hybrid multi-neural system
Anne Canuto1, Michael Fairhurst, Gareth Howells
1Informatics and applied mathematics departament, Federal University of Rio Grande do Norte, Natal, Brazil. anne@dimap.ufrn.br
Abstract:
The set of fuzzy connectives can be seen as an important combination tool, such as in combining the antecedent sets of the rules, in multi-criteria decision making and in combining the outputs of neural classifiers in a multi-neural system. This papers investigates the performance of some fuzzy combination schemes applied to a multi hybrid neural system which is composed of neural and fuzzy neural networks. An empirical evaluation in a handwritten numeral recognition task is used to investigate the performance of the presented fuzzy methods with some existing combination methods.