  Interval type-2 (IT2) fuzzy systems have become increasingly popular in the
last 20 years. They have demonstrated superior performance in many
applications. However, the operation of an IT2 fuzzy system is more complex
than that of its type-1 counterpart. There are many questions to be answered in
designing an IT2 fuzzy system: Should singleton or non-singleton fuzzifier be
used? How many membership functions (MFs) should be used for each input? Should
Gaussian or piecewise linear MFs be used? Should Mamdani or Takagi-Sugeno-Kang
(TSK) inference be used? Should minimum or product $t$-norm be used? Should
type-reduction be used or not? How to optimize the IT2 fuzzy system? These
questions may look overwhelming and confusing to IT2 beginners. In this paper
we recommend some representative starting choices for an IT2 fuzzy system
design, which hopefully will make IT2 fuzzy systems more accessible to IT2
fuzzy system designers.
