A neuro-fuzzy approach with pairwise comparisons
H. Ichihashi, I.B. Turksen · 2002
An iterative learning algorithm in fuzzy models, which is called neuro-fuzzy, has been developed within the framework of fuzzy modeling. Using the neuro-fuzzy approach, two quantification methods of pairwise comparisons are presented in order to derive the associated weights of different objects. The proposed methods can be applied even in the case of incomplete pairwise comparisons. A simplified fuzzy reasoning model is obtained in the form of Gaussian radial basis functions.>