Fuzzy systems design via ensembles of ANFIS

Neurofuzzy networks have become a powerful alternative strategy to develop fuzzy systems, since they are capable of learning and providing IF-THEN fuzzy rules in linguistic or explicit form. Amongst such models, ANFIS is recognized as a reference framework, mainly for its flexible and adaptive character. In this paper, we extend ANFIS theory by experimenting with a multi-net approach wherein two or more differently structured ANFIS instances are coupled to play together. Ensembles of ANFIS (E-ANFIS) enhance ANFIS performance skills and alleviate some of its computational bottlenecks. Moreover, they promote the automatic configuration of different ANFIS units and the a posteriori selective combination of their outputs. Experiments conducted to assess E-ANFIS generalization capability are also presented