As a core part of a fuzzy neural system, the rule base antecedents and consequents may carry uncer- tainties because they are trained using noisy data. So, handling the uncertain rule base is an important need in some specific problems such as noisy non-dynamic problems which leads a better data model- ing. As a solution, Interval Type-II (IT2) version of GSETSK (Generic Self-Evolving ...