« Neuro-flou » : différence entre les versions
(Page créée avec « == Domaine == Category:Vocabulary == Définition == == Termes privilégiés == == Anglais == ===Neuro-fuzzy === <br/> <br/> <br/> <br/> <br/> <br/>... ») |
Aucun résumé des modifications |
||
Ligne 17 : | Ligne 17 : | ||
===Neuro-fuzzy === | ===Neuro-fuzzy === | ||
Neuro-fuzzy hybridization results in a hybrid intelligent system that synergizes these two techniques by combining the human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks. Neuro-fuzzy hybridization is widely termed as fuzzy neural network (FNN) or neuro-fuzzy system (NFS) in the literature. Neuro-fuzzy system (the more popular term is used henceforth) incorporates the human-like reasoning style of fuzzy systems through the use of fuzzy sets and a linguistic model consisting of a set of IF-THEN fuzzy rules. The main strength of neuro-fuzzy systems is that they are universal approximators with the ability to solicit interpretable IF-THEN rules. | |||
<br/> | <br/> |
Version du 1 mars 2018 à 13:38
Domaine
Définition
Termes privilégiés
Anglais
Neuro-fuzzy
Neuro-fuzzy hybridization results in a hybrid intelligent system that synergizes these two techniques by combining the human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks. Neuro-fuzzy hybridization is widely termed as fuzzy neural network (FNN) or neuro-fuzzy system (NFS) in the literature. Neuro-fuzzy system (the more popular term is used henceforth) incorporates the human-like reasoning style of fuzzy systems through the use of fuzzy sets and a linguistic model consisting of a set of IF-THEN fuzzy rules. The main strength of neuro-fuzzy systems is that they are universal approximators with the ability to solicit interpretable IF-THEN rules.
Contributeurs: Claude Coulombe, Jacques Barolet, wiki