Linguistic fuzzy modelling, developed by linguistic fuzzy rule-based systems, allows us to
deal with the modelling of systems by building a linguistic model which could become …

The need for trading off interpretability and accuracy is intrinsic to the use of fuzzy systems.
The obtaining of accurate but also human-comprehensible fuzzy systems played a key role …

Over the past few decades, fuzzy systems have been widely used in several application
fields, thanks to their ability to model complex systems. The design of fuzzy systems has …

This paper aims at providing an in-depth overview of designing interpretable fuzzy inference
models from data within a unified framework. The objective of complex system modelling is …

Fuzzy systems are universally acknowledged as valuable tools to model complex
phenomena while preserving a readable form of knowledge representation. The resort to …

Fuzzy logic is frequently used in computing with words (CWW). When input words to a CWW
engine are modeled by interval type-2 fuzzy sets (IT2 FSs), the CWW engine's output can …

Information granules are complex entities that arise in the process of abstraction of data and
derivation of knowledge. The automatic generation of information granules from data is an …

In this position paper, we are discussing achievements and open issues in the
interpretability of evolving fuzzy systems (EFS). In addition to pure on-line complexity …

Interpretability is acknowledged as the main advantage of fuzzy systems and it should be
given a main role in fuzzy modeling. Classical systems are viewed as black boxes because …

In this paper, we propose an index that helps preserve the semantic interpretability of
linguistic fuzzy models while a tuning of the membership functions (MFs) is performed. The …