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 …

Linguistic fuzzy modeling in high-dimensional regression problems poses the challenge of
exponential-rule explosion when the number of variables and/or instances becomes high …

Fuzzy Rule-Based Systems are appropriate tools to deal with classification problems due to
their good properties. However, they can suffer a lack of system accuracy as a result of the …

In this paper, a multiobjective genetic fuzzy system (GFS) to learn the granularities of fuzzy
partitions, tuning the membership functions (MFs), and learning the fuzzy rules is presented …

In the last years, rule-based systems have been widely employed in several different
application domains. The performance of these systems is strongly affected by the process …

Multi-objective evolutionary algorithms represent an effective tool to improve the accuracy-
interpretability trade-off of fuzzy rule-based classification systems. To this aim, a tuning …

Computing with words (CWW) relies on linguistic representation of knowledge that is
processed by operating at the semantical level defined through fuzzy sets. Linguistic …

Human gait modeling consists of studying the biomechanics of this human movement. Its
importance lies in the fact that its analysis can help in the diagnosis of walking and …

The determination of fuzzy information granules including the estimation of their
membership functions play a significant role in fuzzy system design as well as in the design …