Learning associations between natural groups of input and output with a neurofuzzy structure

A new modeling approach that finds the associations between natural groups of input and output is proposed. In this approach the input and output are clustered separately by means of Fuzzy C-Means (FCM) algorithm that identifies the fuzzy rules by relating the resulting fuzzy sets in input and output spaces by using a neurofuzzy architecture.