title: Fuzzy connectives as a combination tool in a hybrid multi-neural system.
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.
authors.affiliation: Informatics and applied mathematics departament, Federal University of Rio Grande do Norte, Natal, Brazil. anne@dimap.ufrn.br
authors.forename: Anne
authors.initials: A
authors.lastname: Canuto
authors.forename: Michael
authors.initials: M
authors.lastname: Fairhurst
authors.forename: Gareth
authors.initials: G
authors.lastname: Howells
mesh_terms: D001185:Artificial Intelligence; D003198:Computer Simulation; D016001:Confidence Intervals; D019992:Databases as Topic; D003658:Decision Making, Computer-Assisted; D017143:Fuzzy Logic; D006801:Humans; D016571:Neural Networks, Computer; D021641:Recognition, Psychology; D012984:Software