Genetic Design of Fuzzy Neural Networks Based on Respective Input Spaces Using Interval Type-2 Fuzzy Set

In this paper, we propose the genetic design of fuzzy neural networks with multi-output based on interval type-2 fuzzy set (IT2FSFNNm) for pattern recognition. IT2FSFNNm is the networks of combination between the fuzzy neural networks (FNNs) and interval type-2 fuzzy set with uncertainty. The premise part of the networks is composed of the fuzzy partition of respective input spaces and the consequence part of the networks is represented by polynomial functions with interval set. We also consider real-coded genetic algorithms to estimate the optimal values of the parameters of IT2FSFNNm. The numerical experimentation is used for evaluating the proposed networks for pattern recognition.