An Interval Creation Approach to Construct Interval Type-2 Fuzzy Sets

Interval type-2 fuzzy sets (IT2 FSs) are more popular over type-1 fuzzy sets (T1 FSs) as they capture uncertainty in a better way in many real-world problems. Modelling uncertainty with an IT2 FS is relatively complex and solely depends on how to define its Footprint of Uncertainty (FOU)-an uncertainty region of IT2 FS bounded by its lower and upper membership functions. Existing methods either transform existing T1 FSs to IT2 FSs or design IT2 FSs from input data, captured by interval via constructing T1 FSs. In both cases, they require additional processing step and computational time and thus not useful for time-sensitive applications (e.g., intelligent transportation systems, online recommendation systems). To address this limitation, this paper puts forward a simple approach, termed as 'Interval Creation Approach' (ICA) to design IT2 FSs directly from the input data. Further, it is designed to work equally well for transforming existing T1 FS into IT2 FS. The new approach skips data pre-processing phase and the creation of T1 FS as an intermediary to define the FOU of the IT2 FS, thus contributing to faster execution. The paper provides a description of the ICA along with a comparison of its effectiveness against the state-of-the-art methods using both synthetic and real-world data sets.